AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Ralph Idems, Chief Executive Officer at Praevar

The most strategic displays are the ones organizations stop thinking of as just displays. For us in outdoor, transit, campus, and public environments, a display becomes part of the infrastructure. It needs to communicate effectively, withstand demanding conditions, integrate with existing technology platforms and remain serviceable for years—not simply look impressive. That changes how we should evaluate display technology.

Brightness and image quality matter, but so do durability, thermal management, environmental protection, remote monitoring, energy consumption, and serviceability. A display that requires frequent intervention, specialized maintenance, or premature replacement can quickly erase any savings achieved through a lower initial purchase price.

Sustainability and total cost of ownership are increasingly connected. Extending product life, reducing unnecessary truck rolls, and enabling components to be serviced rather than replacing an entire system can reduce both operational costs and environmental impact.

The next opportunity is making these endpoints smarter. Connected displays can provide operators with valuable performance data, while increasingly intelligent content platforms allow organizations to deliver messaging based on location, audience, time, and real-world conditions.

The display is no longer simply where content ends; it is an intelligent, connected endpoint within a much larger communications ecosystem. Organizations that recognize that distinction will stop buying displays for today’s application and start building visual infrastructure for what comes next.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Rick Shaffer, Design Sales Consultant at PCD

A display can be the most visible technology in a room, but visibility shouldn’t be confused with strategy. The real value emerges when displays are part of a thoughtfully designed AV ecosystem.

Consider a college campus: Faculty may need to share content across classrooms, hybrid participants need an equitable experience, administrators need consistent communication across buildings, and technology teams need to manage dozens—or hundreds—of spaces without visiting every room.

The display becomes the common denominator connecting those experiences. But making that experience seamless requires much more than selecting the right screen; network infrastructure, control, audio, collaboration platforms, content distribution, monitoring and support all must work together. We see standardization most valuable across campuses because it can simplify training, troubleshooting, maintenance, and future expansion.

Data adds another layer. System analytics can help technology teams understand how spaces are being used, identify recurring problems, and make better decisions about future investments. AI is increasingly helping to transform that information into actionable insight.

Executive Summary

Shift from Optimization to Transformation: Traditional meeting room design prioritizes operational efficiency and equipment standardization over human experience. By shifting focus from equipping activity to producing desired responses, organizations can elevate in-person gatherings to deliver high-value outcomes.

AI as an Experiential Enabler: AI dramatically reduces the prep, logistics, and customization labor that previously made tailored meeting experiences cost-prohibitive. Agentic AI and smart workplace infrastructure unlock scalable, personalized, and context-aware meeting environments.

Event Production Integration: Physical in-person collaboration must earn its friction by leveraging event production principles—utilizing environmental cues, sensory details, and intentional participant engagement—to maximize ROI on human connection in hybrid workplaces.

I began my career 30+ years ago in theatre production, moved into live events and staging, and eventually into AV and collaboration technology.

Founding NΞXXT has brought those worlds back together for me. Events have become as important to our transformation-enablement mission as our advisory work around permanent collaboration environments. Designing gatherings again, and challenging where the real value sits in a new AI age, has caused me to consistently reflect on what each side of our industry might learn from the other.

We routinely describe events and permanent AV integration as part of the same “AV industry," yet in reality, they operate in very separate silos. Yet looking forward (even more so than looking back) I see far more continuity than separation.

Our work has always been similar in creating the conditions for people to gather around something that matters, then helping them connect, contribute, learn, decide, and act. And I think that mission is only strengthening.

Yet, I keep coming back to one distinction that has driven the divide:

Events are produced around the response we hope to create in people. Meetings have increasingly been equipped around the activity we expect people to perform.

An event producer rarely starts with the technology. They start with people.

Who is coming? What do they already know? What should they understand differently when they leave? What should they feel? What relationships might matter? What decision, commitment, or action do we hope follows?

From there, almost everything can become part of creating that response. Content and participation matter, but events work across a much broader sensory palette: sound and light, food and drink, furniture and materiality, temperature, smell, touch, movement through a space, the welcome someone receives, even what they hold in their hand.

So why do we so consistently fail to think that way in designing collaborative workplace infrastructure, workflows, and environments?

When Optimization Becomes a Constraint

I don’t think the workplace collaboration industry somehow forgot about people. Something much more understandable happened.

As enterprise collaboration matured, many of its constraints became relatively stable. Organizations needed hundreds or thousands of spaces. Technology teams needed to support them. Procurement needed consistency. Users needed simplicity. Budgets needed predictability and efficiency.

So we operationalized. We standardized room types, simplified interfaces, reduced variation, created repeatable deployment models and improved reliability.

When the constraints of any maturing market remain stable, optimization is exactly what we should expect. We refine around what is practical because alternatives carry cost and complexity we cannot justify.

But when the sands shift, opportunity presents itself. As the constraint that shaped an existing model begins to disappear, the question is no longer efficiency. It becomes: what is now possible that was previously impractical?

That is the transition from optimization toward transformation.

Changing the Production Economics

A significant event can justify extraordinary preparation. People spend days, weeks or months understanding audiences, shaping content, briefing contributors, coordinating logistics, creating opportunities for interaction and considering what happens before, during and after the gathering.

An ordinary Tuesday afternoon meeting cannot.

That has always been an ROI calculation. We may know a meeting would benefit from deeper participant context, a different format, stronger facilitation, a more appropriate atmosphere, or better follow-through. But somebody has to decide what would help, then do the work.

Across the volume of everyday meetings inside an enterprise, that human effort quickly overwhelms the potential return.

It’s not the ambition that was necessarily missing. The economics of human effort made it unviable.

This is where I think the AI age opportunity for meetings becomes far more interesting.

AI can increasingly help us understand who is coming, what they know, what they need, where perspectives differ and what might help a particular group progress. That alone will be powerful.

But the events analogy invites us to go further.

What if AI can begin not just changing the administrative effort around a meeting, but the economics of producing the experience?

What should the environment feel like when people arrive? Should it create energy or calm? Encourage exploration or focus? Where might informal interaction matter as much as the scheduled discussion? What role could lighting, sound, furniture, temperature, hospitality, food, materiality, or other sensory cues play in creating the conditions for the response we hope to achieve?

Historically, even considering those questions for an ordinary meeting failed the simplest ROI tests, so we tended to avoid almost any of those explorations.

I recently toured the offices of a high-end financial organization that moved from disposable serving ware toward fine china. Sustainability was part of the rationale, but so was experience. The materiality communicated something about the care, quality and intention it wanted people to feel when gathering there.

Fine china was not going to necessarily create better business decision. But events practitioners understand that human response is influenced by far more than the information we present. Attention, emotion, comfort, energy, trust and connection all contribute. In that instance, someone decided that a sensory detail contributed to that broader experience the organization wants to create. What a great inspiration to build from!

Of course it’s not that enterprises haven’t invested deliberately in the experience surrounding their most important gatherings—consider the CEO’s boardroom, or their executive briefing and customer experience centres. But those were exceptions, because the attention and effort involved was so difficult to scale.

The question now amid AI’s capacity to remove past constraint is whether AI might make more of that intentionality practical at everyday scale, and what technologists might play in that rethink.

Even “yesterday’s smart workplace” infrastructure already understands identity, occupancy, environmental conditions, room configuration etc. Add agentic AI capable of orchestrating some of the planning and adaptation across those systems to the context of meetings and users, and we start entering exciting new territory. To leverage a much broader palette of now experiential amplifiers at a scale where human effort previously made them unviable.

That does not mean making every meeting feel the same as an event. It means learning from an industry that understands how the conditions surrounding a gathering influence what people feel, embrace, and act upon.

Physical Gathering Needs to Earn Its Friction

There is another reason this matters now.

The traditional assumption was that moving from your personal work environment into a meeting room gave you access to something better: larger displays, better audio, better cameras and more specialized technology. Perhaps a compromise in convenience and personalization, but a payoff of broader outcomes in return.

Today that assumption is increasingly questionable.

At home or at a desk, people may have multiple displays, familiar devices, personalized software, tuned workflows and their own relationship with AI. Then they enter a shared space and may be asked to accept a more generic, even reduced experience.

The logistics of gathering also physically faces added friction. Who will be in the office? When are they available? Where can we meet? Does the available space support what we want to do? That’s got substantially harder in a Hybrid workplace.

This may all sound like an argument against physical gathering. Quite the opposite. But we need to raise the standard we expect from it. To recognise and leverage its strengths, not just refine its emerging weaknesses. The point is…

If gathering in person now faces additional friction and greater compromise, the experience of gathering must evolve to offer a return greater than that friction.

A good event does not justify attendance because its projector is better than your laptop. It creates something through people, place, experience and purpose that would be difficult to achieve alone.

Physical presence gives us access to an extraordinarily rich palette of human experience. The opportunity is to use it.

Start With the Experience, Not the Room

Most enterprises already possess much of the expertise required to explore this.

AV and IT teams understand infrastructure, collaboration platforms, reliability and increasingly AI. Events and marketing teams understand audience, narrative, participation, emotion and experience. Workplace and real-estate teams understand physical environments and how people interact with them.

Within the enterprise workplace model we have even seen virtual and hybrid events require some of these disciplines to collaborate, so have some initial precedent. But it seems clear we need to push that alignment further. Not by asking events teams to start specifying meeting rooms or AV teams to become event producers. Instead, bring those perspectives together around a collaborative problem that matters.

Here’s an initiative I propose:

• Choose one important recurring activity. An executive review, project kickoff, product decision, innovation workshop, or learning session.
• Then work future-back for an hour. Assume AI can, or soon could, remove a significant proportion of the preparation, coordination, personalization and logistics effort that historically made greater meeting tailoring impractical.
• Don’t begin with today’s room capabilities. Don’t begin with the latest AI feature on a vendor roadmap.  Instead ask:

If this were an experience we were responsible for producing rather than simply a meeting we were responsible for equipping, what would we do differently?

• What should people understand, feel, decide or do when it ends?
• If the full experiential palette were available, what might we change about preparation, participation, environment, hospitality or follow-through?
• What could become standardized and repeatable? What might intelligently adapt to the particular gathering? Where will human judgement still add the greatest value?

Then work backwards.

• Which parts of that ambition are already possible?
• Which might become practical because AI dramatically reduces the human effort required?
• Which remaining constraints are genuinely technological, and which are process, policy, ownership or simply habit?
• Then find a way to test all that.

The objective is not to predict precisely what meetings will look like years from now. It is to create enough constructive discomfort that we start discovering what is already possible.

When constraints remain stable, we optimize within them. When those constraints erode, we have an opportunity to reconsider the model they created.

Some of the compromises that pushed enterprise collaboration toward standardization, simplification and efficiency were rational responses to what was practical. But we should not automatically preserve every limitation they created.

For me, that is one of the most exciting aspects of this AI moment.

The mission across theatre, events and collaboration technology was never really to install equipment. It was to help people gather in ways that allowed something valuable to happen between them.

That core mission has not changed. The opportunity to fulfil it has.

So my challenge is simple. Before asking what your next meeting room should contain, bring a few different people together and ask:

If the effort required to produce a more relevant, human and outcome-focused gathering no longer faced the constraint it once did, what new experiences would you create?

Then let what you learn challenge everything else.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Brandon White, Director of Product Development at Vanco

Digital displays bring an organization’s visual identity to life: The light, motion, and scale make a deep impression that static displays cannot rival. That said, it takes more than a bright screen with true-to-life color and resolution to capture the attention of today’s audiences.

At Vanco, we’re seeing more and more clients getting creative with their display deployments, even in light commercial contexts. Small businesses, and especially those serving a high-end clientele, need customers to believe in their brand. End customers ranging from wealth management funds to dentist offices are using immersive display deployments to reinforce their messaging and build affinity.

These solutions go beyond simple digital signage or video walls: They use columns and ribbons of displays that flow with architectural sightlines rather than interrupting them, and they use portrait-oriented screens that blend in with high-end aesthetics. They are cultivating an atmosphere. The audience should feel like they are looking at a design feature and not at a TV screen.

Of course, content must be coordinated across every display. As the eye travels from a video wall, to a display ribbon, to a row of hallway signage, the brand experience must remain consistent and in sync. As a result, we have seen a steady rise in AVoIP adoption in small and medium commercial spaces.

The decision to adopt network-based AV distribution is no longer just about sheer scale; end customers at organizations of all sizes need the flexibility AVoIP offers. With a full-featured AVoIP solution, organizations can create video walls with creative layouts; route audio, video, and USB independently; create signage overlays; and more. They have the control and flexibility they need to create a fully immersive brand experience.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Doug Wack, Chief Executive Officer at Total LED

DvLED has fundamentally changed what a display can be. We aren’t limited to conventional screen sizes or formats anymore. DvLED can now transform venues into a storytelling environment, create an immersive command center, energize a venue, or turn an architectural surface into a digital canvas.

There’s another side of innovation that deserves just as much attention: making these experiences practical to deploy. A spectacular display that creates unnecessary complexity in the field isn’t truly optimized. We believe that dvLED should focus as much on the integrator experience as the viewer experience. Cabinet design, mounting methodology, alignment, power and data access, serviceability, and configuration all influence how quickly a system can be installed and how efficiently it can be maintained.

Engineering those considerations into the product from the beginning can reduce installation time, minimize field modifications, and create more predictable project outcomes.

It also changes the total cost of ownership conversation. Faster installation reduces labor costs. Accessible components simplify maintenance. Modular architecture can allow targeted repairs rather than large-scale replacement. And systems designed around repeatable processes make future expansion easier.

The industry will continue pushing pixels, brightness, and visual performance—and it should! But great engineering isn’t just about what the audience sees; it’s about designing a display that delivers an incredible experience while making life easier for the people responsible for installing, operating, and maintaining it.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Elijah Mounts, Product Manager at Mount-It! PRO

When we talk about the future of displays, the conversation gravitates towards what people can see: larger canvases, finer pixel pitches, immersive content, and increasingly sophisticated visual experiences.

But I think some of the most important decisions happen behind the display. A mounting system determines far more than where a display sits on the wall; it can affect installation time, accessibility, ADA compliance, alignment, serviceability, labor requirements, and, ultimately, the total cost of ownership of the system. That becomes even more significant with dvLED.

A stunning dvLED wall depends on precision. Small inconsistencies across a large array can become highly visible, which makes adjustment and alignment critical. At the same time, integrators are being asked to complete increasingly sophisticated installations with tighter timelines and limited skilled labor.

Mounting technology has to evolve alongside the display. Modular designs, micro-adjustment, fewer components, and easier front or rear service access can help integrators turn complex installations into repeatable workflows. And when a technician can access, adjust, or replace components without dismantling major portions of an installation, those efficiencies continue long after commissioning.

The mount may never be the star of the visual experience, but if it’s doing its job, it makes everything in front of it look better and everything behind the scenes work smarter.

As I prepare to launch a new brand under the AVNetwork umbrella, Workplace AI (more on that soon), I am consuming more content on the topic of AI than ever before—if that's even possible.

​On Oct. 21, in the midst of prepping an article to post on AVNetwork.com, our CMS went offline because of the worldwide PHP vulnerability. Cybersecurity firm Calif and cloud security firm Wiz discovered the vulnerability using AI tools from OpenAI and Google. We've come to know that it affected approximately 70 percent of websites globally. Miraculously, thanks to our engineering and IT teams, I was back up and running in less than an hour.

The world is still abuzz when, in September, ex-Anthropic employee Jacob Coxon declared on X, “The people building AI earnestly believe that it could kill us all by the end of the decade.” Then, to put a finer point on it, Evan Hubinger, a current team lead at Anthropic, responded, “Jacob is correct here—we really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade. I believe Anthropic is trying its best, but we do not yet have a plan to solve alignment for superintelligence and are not clearly on track to.”

As I plan and create content for Workplace AI, I am focused on the benefits of the here and now, and I am excited.

Coincidentally, on Oct. 21, Anthropic's co-founder, president, and chair of the board of directors, Daniela Amodei, posted to LinkedIn the foreword she wrote to the company's recently released charter, Anthropic Public Benefit Report.

The report comprises five pillars, with the first pillar being, “The technical problems of AI safety are solved,” which is a particularly bold objective.

In her foreword, Amodei touted the many successes organizations have reported using Claude, such as: “In the lab, Claude designed new protein binders from scratch. In Burkina Faso, a team with the International Rescue Committee asked Claude to turn clinic registers into digital dashboards. Those dashboards flagged a spike of 25,000 pneumonia cases, so the team can anticipate and plan for future surges. A lawyer in India who feared the dense prose of Shakespeare began reading 'Hamlet.'"

Amodei is quick to point out the potential and real pitfalls: “AI is a dual-use technology. The same intelligence that powers protein binder discoveries could be used by malicious actors to engineer biological weapons. Without appropriate safeguards and release structures, cyber capabilities could be exploited to carry out large-scale attacks instead of serving to strengthen our infrastructure. If not properly trained and carefully deployed, AI can be a danger in its own right.

For these reasons, Anthropic has a duty to ensure our models are robustly safe and aligned with human values and goals.”

Personally, I am holding out hope that companies such as Anthropic, OpenAI, and others are able to build models that ensure humanity first.

The Safety Pillar

The full 20-page report is worth reading, but the transparency outlined in detail by Anthropic in the first pillar is sobering and should be food for thought for all of us.

Pillar 1: The Technical Problems of AI Safety are Solved, ends with the following statement: “The same safeguards that prevent our models from being exploited by attackers and other malicious actors can sometimes also prevent the beneficial work of defenders and researchers. Our bio and cyber verification programs are meant to reduce these roadblocks for verified users, but the review process can take days or weeks, and the programs are not yet available on every plan or platform. We have made improvements to our safeguards that have reduced false positives, but many legitimate researchers still encounter blocks.”

Read the Anthropic 2026 Public Benefit Report.

Today, Tomorrow, and

If there’s such a thing, I am a cautious Pollyanna. I am hopeful that humanity will win.

And in my current world, writing about, illuminating stories, and helping to enlighten my readers about how AI can help enhance the collaborative workplace (which is anywhere you work) is what has me super excited. Stay tuned!

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Misty Chalk, Vice President of Sales, Americas at BrightSign

Audience expectations for engaging experiences have heightened in recent years. Immersive, interactive activations were once limited to entertainment venues. Now, advances in display technology and digital signage players have made dynamic audience interactions a priority across industries—from banks and retail stores to corporate offices and quick-service restaurants.

As organizations invest more in digital displays as a revenue driver, they’re looking to optimize the value of every visual touchpoint. That’s where AI is offering the greatest impact and driving more tailored, customized content. AI-powered gaze detection, for instance, can help organizations measure how many people engaged with one visual versus another. Meanwhile, AI can also help detect content anomalies, such as incorrect aspect ratios and blank screens, helping AV teams quickly identify a fix to minimize downtime. To gain the most benefit from these AI-powered tools, it’s important to consider the type of media player you have processing content. A player with a built-in Neural Processing Unit (NPU) can run powerful AI applications directly on the device so users don’t have to worry about sacrificing performance.

Similarly, as digital signage networks grow larger and more distributed, centralized management becomes essential. Whether managing displays across a college campus or nationwide enterprise, AV teams need access to comprehensive management tools that give them visibility into the entire network. An effective management solution will support the ability to scale, monitor, and schedule actions across a fleet of players.

Ultimately, maximizing the return on display investments isn’t just about adopting the latest AI capabilities; it requires building an ecosystem that is intelligent, scalable, reliable, and secure so organizations can focus on delivering an innovative, memorable experience.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Kurt DeYoung, Chief Revenue Officer at Nanolumens

Engaging and immersing audiences is all about making a good first and lasting impression. From the viewer experience perspective, not a lot has changed regarding what draws eyes, engrosses, and creates memories: It is size, resolution, color accuracy, brightness, and even shape. Content remains king, but if the display is big, bright, crisp, colorful, and a non-standard shape, then it’ll most likely be memorable. The more-than-200-square-foot, cone-shaped Oculus LED display at Houston’s George Bush Intercontinental Airport is a prime example of this. The Oculus is huge, features incredible content on a non-traditionally shaped canvas, and is interactive.

However, organizations must evaluate display technology beyond specifications—and instead make displays a piece of the broader environment’s look, feel, and function. Often, environments incorporate natural and practical elements such as trees and stones so the atmosphere is not fully digital—and need display technology to amplify and support the spirit of the space.

From a behind-the-scenes perspective, organizations are placing greater emphasis on display solutions that can evolve alongside their operational needs. Whether in higher education, corporate, museums, or public venues, immersive environments are most effective when displays integrate seamlessly with content management, collaboration platforms, and control systems. As a result, organizations can deliver consistent experiences across multiple locations while simplifying content distribution and system management.

The most successful deployments recognize that displays are part of a broader ecosystem. Close integration with video processing, content management, and collaboration technologies creates environments that are easier to deploy, manage, and expand as organizational needs change. Rather than focusing solely on display specifications, organizations should evaluate how technology supports long-term flexibility, operational efficiency, and audience engagement. An ecosystem approach helps create immersive experiences today while ensuring systems remain valuable and adaptable for years to come.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: John Tracy, Senior Vice President of Sales at SiliconCore

One of the most significant developments in display technology is the rise of the all-in-one LED display. It is making fine-pitch LED accessible to a much wider range of organizations by removing much of the complexity traditionally associated with deploying LED.

Rather than designing a display permanently into one room, organizations can now deploy large-format LED without a lengthy installation process and, with mobile solutions, move that investment between collaboration spaces, training rooms, engineering environments, and multipurpose facilities as requirements change.

That versatility changes the TCO conversation. A display that can serve several spaces and applications has the potential for much higher utilization over its lifetime. It also gives IT and AV teams greater flexibility to respond to evolving workflows without continually redesigning rooms around fixed technology.

However, simplicity at the front end shouldn’t mean overlooking what’s happening behind the display. As LED canvases become larger, power consumption and heat generation become increasingly important considerations for both operating cost and sustainability.

When specifying a solution, look beyond pixel pitch, resolution, and brightness to how efficiently the LEDs themselves are being driven. Technologies such as Common Cathode independently manage the voltage supplied to the LEDs, reducing wasted energy and heat.

That can have a tangible infrastructure benefit. Highly efficient all-in-one displays can operate from a single standard power connection without additional components adding more electrical and cooling requirements. The more integrated the product—the fewer potential points of failure.

The opportunity is to make LED not only more accessible, but more usable as a flexible resource that can move with an organization while consuming less energy throughout a longer operational life.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: James Pietsch, Director of Global Accounts at Scalable Display Technologies

Projection technology has expanded beyond display content and has, instead, become part of a connected AV ecosystem that supports collaboration, immersive experiences, and centralized management across a wide range of environments. Whether used in corporate campuses, higher education, museums, or training facilities, organizations are looking for projection systems that are easy to deploy, simple to manage, and built to scale.

Large-format projection continues to be one of the most effective ways to engage audiences. Higher brightness, improved color performance, and advanced image processing enable immersive experiences in spaces where traditional displays are impractical or cost-prohibitive. Networked projection systems also allow organizations to share content across multiple rooms or campuses, helping ensure a consistent experience regardless of location.

AI is beginning to play a larger role behind the scenes. Rather than replacing operators, it helps automate tasks such as image optimization, scheduling, and system monitoring while providing insights into room usage and content performance. These capabilities help organizations make better decisions while reducing the time required to manage complex AV systems.

Just as important is interoperability. Projection platforms that integrate with collaboration platforms, content management systems, and cloud-based monitoring tools simplify workflows and allow administrators to manage multiple systems from a single interface.

Organizations are also placing greater emphasis on sustainability and long-term operating costs. Laser light sources reduce maintenance by eliminating lamp replacements while improving energy efficiency and product lifespan. Combined with remote monitoring and centralized management, these capabilities reduce service calls, minimize downtime, and lower the total cost of ownership. As projection technology continues to evolve, its value extends well beyond image quality to supporting more efficient, connected, and sustainable AV environments.

In October, US federal prosecutors charged an OpenAI engineer with planting an audio recording device in an executive conference room at the company's San Francisco offices. According to the complaint, the device was wrapped in toilet paper and plugged into a USB port on the back of a television. OpenAI says its technical surveillance countermeasures team found it during a room sweep.

A sweep of the room found it. Nothing on the network did.

That should bother the Pro AV and IT industry. Most of our security conversation is about VLANs and access control. All of that matters, and none of it would have caught this device. The case sits in the gap between physical security, AV operations and IT, where ownership blurs.

Know What Belongs on the Network

Most AV teams can scan a subnet. Tools such as LanScan or Angry IP Scanner are useful during commissioning and fault-finding. They show which addresses respond and turn up obvious surprises. A scan is a snapshot, though. It can't tell whether a device is authorized, who owns it, or whether something new appeared five minutes later. A device can stay silent or sit on another interface. It can also record locally and never touch the network.

AV networks need what any enterprise network needs: continuous comparison between the expected estate and the observed one. For every AV VLAN, the operator should know each approved device, its role, location, switch port, MAC address, firmware level, owner and normal traffic pattern. Switch telemetry, passive discovery and light active checks should flag new endpoints and material changes as they happen. Periodic audits are still relevant, especially after room changes or service visits. They verify the system, but they shouldn't be the main defense.

When an unknown endpoint appears, the network should restrict it automatically, move it to a quarantine segment and alert its owner. Network access control (NAC), port policies and device profiling do this today. In high-risk rooms, you should disable unused switch ports and USB power, or physically secure them.

Here's the test I'd apply. Can the AV team say what belongs on the network, and cut off anything that doesn't within minutes? If not, it can see the network but can't control it.

It Could Have Been Worse

Now suppose the device had ignored the corporate and AV WiFi and sent its recordings out through a personal mobile hotspot hidden in the same room. An IP scan would still show nothing.

Wireless intrusion detection could catch it. Rogue access point monitoring watches the RF environment, so it can spot an unapproved hotspot and suspicious associations even when the traffic never reaches the enterprise LAN. The system should tell that hotspot apart from legitimate neighboring networks, alert security and keep enough evidence for an investigation. A device that transmits only now and then is harder to catch, but continuous monitoring still narrows the window.

Remote Access Without Exposing the Room

Remote support saves truck rolls and gets rooms working again faster. It can also turn every device web interface into a way in.

Forwarding a port straight to an encoder, DSP, controller or display is indefensible. So is a broad VPN that gives a technician the equivalent of a cable into the whole AV subnet. Many AV devices were built for trusted local networks. Their web interfaces often run old protocols on firmware that can't be patched quickly.

The safer standard is brokered access to a named device or management controller. The session starts with an outbound encrypted connection. It requires single sign-on and multifactor authentication, grants time-limited permissions by role, and logs every action. Shared installer accounts should go. Access should be approved for a specific job and revoked when the job is done.

NETGEAR uses this model for the NETGEAR Align Controller. NETGEAR Insight brokers remote access into the local controller, so support teams reach the management function without exposing the AV network to the internet.

Brokered access has trade-offs. It adds a dependency on a cloud service and on the vendor running it securely. Customers should ask where credentials and telemetry are stored, how access is revoked, whether logs can be exported, what happens during an outage, and who tests the service independently.

Set Policy at the AV-IT Boundary

Segmentation is essential, but address-and-port firewall rules are a blunt tool between AV and enterprise IT. They don't know which multicast flows are legitimate, or whether a support session was authorized for a specific endpoint.

AV systems depend on discovery, multicast, timing and dynamic relationships between services. The common fix is to open a wide range of ports between VLANs. That restores function by gutting the boundary. It's like leaving every door unlocked because you'd rather not carry keys.

The better approach ties policy to what each device is for. A room controller can reach its own management service. A support engineer can reach one endpoint for a set period. None of those permissions should open general access to the corporate network. Most enterprises already own the tools for this. NAC and segmentation policy need to be set up with AV traffic in mind.

This takes more design work. Some AV protocols won't fit neatly, and every enforcement point adds a dependency in the signal path. Test the policy against real AV traffic before go-live, and write down what happens when a component fails. Whatever enforces the boundary is security infrastructure, and it needs to be run that way.

Make Security Part of Handover

The OpenAI case shows the answer can't stop at the network. High-value rooms need physical checks as well. Integrators are well placed to build those checks into commissioning and acceptance.

Before sign-off on a high-value room, the handover pack should include:

• A device inventory for every AV VLAN, matched against what the switches actually see
• A record of connected peripherals, including anything plugged into display USB ports
• Unused switch ports and USB power disabled or physically secured
• Documented remote access: who can reach which device, through what, and how access is revoked
• Tamper-evident seals on displays and racks where the risk justifies them
• A named owner in IT and in corporate security for alerts from AV systems

Repeat the physical and inventory checks after every service visit or room change.

Today, nobody clearly owns the space behind the screen. The integrator knows the room, IT owns the network policy and corporate security owns the evidence. A shared handover checklist is a cheap way to give that space an owner.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Roberto Musso, Senior Technical Director at NDI

A display becomes strategic when it stops being the end of a signal chain and starts participating in a two-way workflow.

In an NDI-based environment, video and audio are only part of the exchange. Metadata can travel with the media, carrying identity, capabilities, status, timing, and control information. This allows content not merely to play, but to respond. A touch interface can request a different source, room or event data can trigger a content change, and authorized teams can monitor and control supported endpoints across buildings or campuses.

AI can help determine which content may be relevant, but metadata provides the operational context needed to act on that decision, and can carry the feedback needed to assess the result. This distinction matters: Intelligence can remain in software and evolve without turning every display into a closed, single-purpose appliance. Privacy, permission, and transparency must be designed into the workflow—especially when audience data is involved.

For AV/IT teams, flexibility, and total cost of ownership come from consolidation and reuse—not from IP alone. A shared NDI infrastructure can support media distribution, monitoring, control, and interaction while reducing dedicated signal paths and specialized hardware. However, bandwidth, energy use, resilience, security, and maintenance still need to be measured across the complete system.

The strategic display is therefore not the screen with the longest feature list; it is a connected participant that can receive media, expose its state, accept permitted control, and help turn one-way messaging into a responsive experience. That is how display systems become easier to operate, adapt, and scale.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: David Albright, Senior Product Manager, Video Wall Mounts and Services at Legrand | AV, Chief

The display is no longer a single screen in a single room; it is the strategic centerpiece of how organizations engage audiences, from a dvLED wall in a lobby to a campus-wide network of displays. A display is only as strategic as the infrastructure holding it up.

Immersive, seamless dvLED experiences depend on precision alignment across three axes—not a flat wall and a bracket. Buildings shift, walls are rarely plumb, and fine-pixel-pitch displays reveal every imperfection. Mounting systems engineered for independent X, Y, and Z adjustment let integrators deliver a seamless wall on day one and keep it that way as a building settles.

That same infrastructure layer underpins how organizations standardize operations. A single, cross-manufacturer mounting platform replacing brand-specific hardware gives campuses and multi-site portfolios one specification and installation workflow at every location, regardless of display brand, reducing training time and simplifying inventory.

It also drives total cost of ownership. Front-service access for realignment means a display can be serviced in place rather than pulled down and reinstalled, extending usable life and reducing rework and downtime as new applications place demands on displays.

The same is true for power. Legrand | AV’s Unified Cloud Platform consolidates remote monitoring and management into a single view, whether the load is one display or a full video wall plus the edge devices delivering the content behind it. Across enterprise and higher-education campuses, that visibility is what sustains performance and serviceability over the installation’s lifecycle.

As displays take on more strategic, data-driven roles, that infrastructure cannot be an afterthought. Getting the physical and digital foundation right is what lets everything else—from immersive content to connected ecosystems—perform as intended.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Chris Teguh, Product Manager at Epson America

Technology plays a foundational role in creating engaging and immersive experiences, determining the clarity, accuracy, and impact of the presented content. Advances in color brightness, color accuracy, and resolution in today’s displays help ensure digital content appears vivid and true to life to capture attention and foster engagement. At the same time, smaller form factors, versatile throw ratios, and greater installation flexibility enable large, impactful visuals in spaces where they previously weren’t feasible. This opens new opportunities to transform unconventional environments into more immersive, memorable experiences that connect people more deeply to the content.

When selecting display technology, organizations can benefit from focusing on common operating standards, consistent user experiences, interoperability, and centralized management. Consistency can also extend to how content is created, distributed, and measured. Within a connected ecosystem, AI can help tailor messaging for different audiences and locations, while data provides insight into how content is performing.

Standardization also allows users to move seamlessly from room to room without learning new systems or workflows, while enabling consistent content sharing, hybrid collaboration, and centralized IT management across locations. Total cost of ownership should be evaluated across the entire lifecycle, not just purchase price. This means looking at installation, energy use, maintenance, training, replacement parts, and operational downtime.

Innovations across both projection and dvLED are improving efficiency to get the greatest long-term value from technology investments. Laser projection technology and filterless designs reduce maintenance, extend product life, and lower operating costs, while COB technology and common cathode designs in dvLED solutions help reduce power consumption and heat generation. Together, these advances give organizations more ways to create impactful experiences that support stronger communication, participation, and engagement.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Aaron Addison, Senior Manager, IT Corporate Leader at LG Electronics

A good display strategy starts with looking at the whole environment—not just the individual product. IT teams are trying to create standards that are easier to deploy, easier to manage, and give users a consistent experience whether they’re in an office, a classroom, a collaboration space, or somewhere else across the organization.

The biggest thing I hear from customers, corporate and higher ed alike, is that everything has to work together as one digital asset strategy: hardware, software, services, connectivity, security, and device management planned as infrastructure and not as point purchases bolted on later. That starts with the OEM relationship itself. They want a partner who’s driving initiatives and bringing collaborative solutions to the table—not just selling boxes. Bring that partner in at the design stage and you avoid systems forced into rooms never meant to support them.

That’s also where total cost of ownership really comes into play. It’s not just about what a display costs on day one. Customers are looking at reliability, lifecycle, manageability, and how much time their IT teams are spending supporting the technology over several years.

AI is obviously becoming a bigger part of the conversation as well. There are some great opportunities around smarter management, understanding usage, and delivering more targeted experiences, but most organizations still need to get the fundamentals right first.

At the end of the day, technology should make things easier for IT and better for the person using it. If it does both, then you’re probably headed in the right direction.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Amber Ward, Senior Marketing Director at Carousel Digital Signage

Engaging digital signage isn’t just eye candy; it’s about purpose. Kinetic lobby displays are great for setting a vibe, but function must come first. If a digital menu shifts to an announcement right as a customer is trying to order, the signage fails. Start with the goal and the audience, then build content that serves both.

Effective engagement requires balancing the needs of both the audience and the content creators. In large organizations, like university campuses, relying on a single contributor often misses nuances. A more efficient workflow distributes authorship to individual departments, ensuring content is authentic and accurate. Digital signage software with role-based permissions enables a streamlined approval process: Contributors create updates, and administrators review messaging before it goes live.

One way to maximize the cost of a growing digital signage system is to invest in software that works well with mixed-device environments. High-quality digital signage platforms work with many popular dedicated media players, integrated displays, software-based players, and remote management systems, giving the end user choices. When you can leverage your own devices and manage them at scale while keeping your environment secure, the possibilities open up and total cost of ownership goes down.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Jim Vasgaard, AV Sales Manager and Business Development at Daktronics

Choosing a reliable U.S.-based dvLED display manufacturer can eliminate information gaps that often slow complex installations and service uncertainty for your display’s lifetime. AV/IT end users who work with a manufacturer they know and trust receive access to consultative U.S.-based sales staff that can quickly pull in project managers and engineers when questions arise about product capabilities, electrical requirements, signal routing, or unusual installation conditions.

Product knowledge is a key differentiator. Look for reputable companies that understand the LED technology they’re delivering. There is an overflow of differing indoor LED packaged solutions in the market today, and truly understanding each solution—their pros and cons—can be difficult in the purchasing process. Look for manufacturers who handle design, testing, manufacturing, and service in-house, and staff a team that can speak about how a system will perform in the field—and match the right product to the application from the start.

Find out if they operate their own testing lab where components are tested to failure during the design phase, giving engineers a clear picture of how each part will behave over the life of the display.

That testing discipline also extends to supplier management. If the manufacturers’ suppliers make any changes to the system, that dvLED manufacturer needs to know about it and be able to test it before they make that change and ship a new display solution using that component.

And finally, make sure your dvLED manufacturer stands behind and supports its product for its lifetime. Ask about parts access guarantees that reach 10 years to ensure you receive full support for the lifetime of your display. The goal should be that you receive a display system that arrives on time, delivers on day one, and performs predictably and dynamically throughout its life.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Joel Mulpeter, Senior Director of Product Marketing at Crestron

As far as this segment’s concerned, the products we make at Crestron move content and ready it for the display, whatever that might be. With solutions such as DM NVX AV over IP, we can help ensure that the signal is lossless, reliable, secure, and moved at near-zero latency. The goal is to deliver the best possible experience—no matter the vertical and no matter the screen—whether it’s a Jumbotron at a sports venue, signage in a retail space, or the screen in a huddle room.

To do that, we need to deliver more than a black box; we need to deliver a system that’s future-ready—specifically, that is, able to handle needed firmware updates.

We strive to provide products that can essentially function anywhere—not on a room-by-room, case-by-case basis. The best and most versatile solutions lean into building- or campus-wide network infrastructure that will reduce the need for rip-and-replace solutions in the future. If you can swap out a single encoder-decoder or change a screen at an endpoint to suit the changing needs of a space, the right network infrastructure will deliver the best experience no matter how the display hardware may change.

When you have that network architecture in place, other options open up: You can switch any content to any endpoint in the building, and you can monitor everything in the same, consistent way. Control doesn’t change from space to space or building to building, either; it remains familiar to the user throughout the organization. Furthermore, your IT and AV staff will have that same kind of familiarity, no matter the space—and that’s bound to save time and money should an issue pop up.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Daniel Renne, Director of Emerging Technologies at Hall Technologies

For decades, we have thought of the display as the destination in the AV signal chain. Content travels through an increasingly sophisticated technology ecosystem, but ultimately the display has one job: present that content to the audience. I believe that definition is rapidly changing.

The next generation of displays should become intelligent participants within the broader enterprise technology ecosystem. Cloud connectivity, IoT technologies, and AI give organizations an opportunity to better understand not only what content is being displayed, but how, when, and where their AV environments are being used.

That intelligence can fundamentally change the audience experience. Digital signage can adapt messaging based on location, time, events, occupancy, or other organizational data. Across campuses, centralized platforms can coordinate content and experiences while still allowing individual spaces to respond to local needs.

The same data can provide tremendous operational value. Understanding display utilization, operating hours, device health, energy consumption, and content effectiveness can help AV and IT teams identify problems earlier, automate workflows, reduce unnecessary energy usage, and make better lifecycle decisions.

AI will accelerate this transformation, but its effectiveness will depend heavily on the quality and context of the data available to it. The goal should not simply be to add AI to displays, but to build an ecosystem where displays, AV devices, cloud platforms, and enterprise systems can securely share meaningful information.

Ultimately, maximizing the value of a display means looking beyond resolution, brightness, and specifications. The most strategic display may be the one that helps an organization better understand, automate, and continuously improve the environment around it.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Martin Kuhn, Vice President of Experiential Technologies at Ross Video

Displays are no longer just endpoints; they are the connective tissue of live experiences. From stadiums and corporate campuses to museums and multipurpose venues, every surface can become part of a connected story, with LED, projection, audio, lighting, control, and data working seamlessly together.

That matters because audiences now expect experiences to respond to where they are, why they are there, and what is happening in the moment. AI and analytics can help teams understand traffic patterns, content performance, and audience interests, but the real value comes when those insights can be translated into targeted, repeatable content workflows: the right message on the right canvas at the right time.

With Vertex, we see an immersive display strategy moving toward unified ecosystems. A campus can support a town hall in one space, branded wayfinding in another, and a large-scale evening activation elsewhere—all with simpler operation and consistent creative control. For venues, that means synchronized fan moments across boards and displays. For cultural or brand environments, it means sensor-driven interactivity and projection-mapped storytelling where the technology fades into the background.

This approach also improves sustainability and total cost of ownership. When systems are easier to automate, reuse, scale, and support, teams can reduce one-off engineering, limit redundant equipment, extend the useful life of installations, and operate sophisticated experiences without oversized crews. The future of display is not just brighter pixels; it is smarter orchestration.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Rudy Vitti, Group Manager of Product Marketing at Panasonic Projector & Display Americas

Display technology is becoming more influential across environments—from campuses and corporate spaces to arenas, restaurants, and retail outlets. Display screens have evolved from simplistic digital poster boards into immersive storytelling tools that engage audiences, streamline communication, and support operations. Flat panel displays deliver bright, color-accurate visuals for live feeds, wayfinding, messaging, and digital signage, while dvLED creates seamless, large-scale experiences in lobbies, command centers, and other signature spaces.

For organizations managing multiple buildings or venues, consistency and connectivity are key. Standardized displays and centralized content management can create a cohesive visual experience across a campus while simplifying AV/IT management. An integrated ecosystem also allows organizations to build on existing infrastructure rather than replace it, enabling new displays to work alongside LCD video walls, projectors, and other legacy technologies.

AI can further enhance these networks by helping teams deliver the right message to the right audience at the right time. Location- and time-aware content scheduling can support targeted messaging, safety alerts, wayfinding, event promotion, and sponsorships, while engagement and usage data can inform future facilities, marketing, and content decisions.

Just as important is designing technology for long-term value. Some dvLED solutions can be designed to integrate easily into existing infrastructure, reducing upfront investment. DvLED simplifies servicing, allowing teams to replace components rather than an entire display, while all-in-one solutions can streamline installation by arriving pre-assembled and pre-calibrated. Displays engineered for 24/7 operation and centralized management can reduce downtime and maintenance over time. Together, these approaches help organizations create more immersive experiences while improving workflows, supporting sustainability through longer equipment lifecycles, and maximizing total cost of ownership.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Trent Slyter, National Sales Director of Pro AV Sales at Absen

Not long ago, displays were often viewed as the final component of an AV project—the technology used to present content after the real decisions had been made. Today, that mindset is changing. Across industries, displays have become strategic assets that shape how organizations communicate, engage, and deliver on their mission.

Consider the range of environments AV/IT professionals support today. In higher education, displays help create more collaborative and accessible learning experiences. In corporate offices, they enable communication that connects distributed teams and reinforces culture. Retailers use displays to capture attention and influence purchasing decisions, while hotels, casinos, resorts, and cruise ships rely on them to elevate the guest experience. In sports venues, displays energize fans, deliver real-time information, and create new sponsorship opportunities. In houses of worship, they help ensure every member of the congregation can clearly see, connect with, and participate in the message.

While the applications differ, the objective is remarkably consistent: help people engage more effectively with the experience in front of them.

That shift should change how AV/IT leaders evaluate display technology. The conversation can no longer begin and end with size, brightness, or resolution. Strategic display investments are measured by how well they adapt to evolving needs, integrate with broader technology ecosystems, support multiple stakeholders, and continue creating value over time.

The display is no longer simply where content appears; it has become one of the most important touchpoints between organizations and their audiences. The most versatile display isn’t the one that can show the most content; it’s the one that helps an organization communicate, connect, and fulfill its mission—no matter how that mission evolves.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: Joe Drury, Senior Business Manager, BRAVIA Professional Displays at Sony Electronics

The role of the professional display has changed dramatically. What was once an endpoint for content delivery has become a platform for communication, collaboration, audience engagement, and business intelligence.

As technology requirements continue to expand, it has become increasingly difficult for any single manufacturer to provide a complete end-to-end solution. Today’s deployments depend on ecosystems that bring together hardware, software, analytics, content management, and collaboration tools. The success of a display is no longer defined solely by its specifications, but by how effectively it integrates into that broader environment. At Sony, this perspective continues to shape our Pro BRAVIA strategy, emphasizing interoperability, flexibility, and ecosystem partnerships.

This shift began with BYOD and the demand for greater flexibility. Today, spaces are no longer defined by how they were originally designed, but by how users need them to function throughout the day. A single environment may support collaboration, digital signage, training, or targeted communications depending on the moment. Artificial intelligence is accelerating this evolution by helping organizations automate workflows, deliver more relevant content, and gain insights from operational data.

At the same time, AV investments are becoming more strategic. Reliability, sustainability, serviceability, and lifecycle value are increasingly important, yet many of these attributes remain difficult to quantify and specify. Customers recognize that factors such as image quality, operational efficiency, and manageability impact outcomes, but they are often evaluated as commodities. The industry must do a better job helping customers define and specify the capabilities that matter most.

At Sony, we believe our responsibility extends beyond delivering products; it includes helping customers define success, identify what matters most, and build solutions that continue creating value long after installation.

AVT Question: Please share insights on how to immerse audiences, collaborate across campuses via the cloud, use AI to drive targeted messaging and gather data, increase sustainability, and reduce total cost of ownership.

Thought Leader: John Kruse, Solutions Engineer Manager at ViewSonic

Today’s commercial display is simply no longer the endpoint of an AV system; it has become an integrated platform within an organization’s broader technology ecosystem. How well it integrates, how easily it can be managed, and the operational value it delivers over time matter as much as what it displays.

Modern displays integrate into collaboration, digital signage, cloud management, and room control ecosystems to create consistent user experiences across offices, campuses, and distributed environments. That interoperability reduces deployment friction, simplifies ongoing support, and gives AV and IT teams the visibility they need to manage at scale.

Total cost of ownership tells a more complete story than acquisition cost alone. The display that wins the proposal isn’t always the one that delivers the most value in year three or year five; integration complexity, management overhead, software compatibility, and lifecycle support factors in what a deployment actually costs an organization over time.

Proprietary ecosystems create dependency. Open, standards-aligned platforms create flexibility.

And flexibility compounds value over the life of the deployment.

Artificial intelligence is accelerating this evolution by making displays more than presentation devices. Predictive diagnostics, usage analytics, and automated content optimization reduce operational burden on lean teams—returning value not from the moment of purchase, but across the years that follow.

The most successful display strategies recognize that hardware specifications are a starting point—not the deciding factor. Ecosystem alignment, remote manageability, and long-term supportability increasingly determine which investments hold their value.

The display on the wall is no longer just a screen; it’s an operational platform.

Executive Summary

• Network Convergence and Standardization: Pro AV is increasingly integrating with IT infrastructure through open standards like IPMX, shifting market value from hardware ports to network orchestration, lifecycle management, and interoperability.
• AI Integration vs. Component Constraints: While embedded edge AI enhances smart AV capabilities, massive data-center AI expansion has constrained memory supply (DRAM, NAND, HBM), increasing component cost volatility and supply chain risks for manufacturers.
• Shift to Recurring Service Models: Global geopolitical friction and tariff structures are making hardware-only sales less predictable, driving integrators toward managed services, continuous remote monitoring, and software-defined recurring revenue models.

Nearly a year ago, I argued that ten growth opportunities would define Pro AV: from AV over IP and broadcast convergence to intelligent surveillance, cloud signage, managed services, and emerging markets.

The direction was right. But the market has gotten less forgiving. Growth is still available. It's just not easy anymore.

The Network Story is Stronger

AV over IP has continued its move from alternative architecture to default assumption. Broadcast and Pro AV are converging too, as common, open standards get easier to deploy. The first formal IPMX certification wave, at ISE in February, covered 48 products from 11 manufacturers; a second event in August added 14 more from eight manufacturers. It's a slow process, but an important one. Certification reduces multi-vendor risk and gives customers a credible path away from proprietary lock-in.

The pixel explosion remains real across stadiums, control rooms, and large-scale LED. So does the move to multi-gigabit, 25/100/400GbE infrastructure. But bandwidth alone is no longer the differentiator. Operations make the difference. Customers are more vocal about topology visibility, audit trails, fleet management, and rapid recovery. If you can’t diagnose a network remotely, you have an expensive support problem.

Margin is migrating from ports and endpoints toward orchestration, support, and lifecycle services.

AI Became Both an Accelerator and a Constraint

Last year, AI was most visible in surveillance analytics. Now it reaches almost every opportunity. Cameras frame speakers automatically. Meeting-room agents take notes and manage audio zones. Signage adapts content using audience data. AI assists design, programming, and fault diagnosis. At InfoComm 2026, AI was moving from a cloud feature to an embedded agent capability at the edge.

That expands the addressable market for intelligent AV, but it also raises expectations. Buyers will ask whether an AI feature cuts labor, improves utilization, or increases revenue. If the answer to one of those questions isn’t yes, it's not a business case.

AI has also created a supply-side paradox. The data-center buildout is absorbing high-bandwidth memory and pushing manufacturers toward their most profitable, priciest products. Micron's fiscal second-quarter results, reported in March, showed revenue climbing from $8.05 billion to $23.86 billion year-on-year on strong demand and tight supply. Conventional DRAM and NAND buyers are competing for the same constrained output; SK Hynix said in January it had already sold out its entire 2026 HBM, DRAM, and NAND output.

For AV manufacturers, that means more volatile component costs, redesign pressure, and harder allocation decisions. For integrators, it means shorter quote validity, substitution risk, and a renewed premium on vendors with dependable supply. Intelligence at the edge will keep growing, but at a higher price than we anticipated.

Geopolitics Changed the Route to Growth

The case for emerging markets still stands, but "go global" is too blunt. India, Southeast Asia, the Middle East, and Latin America benefit from infrastructure investment and demand for immersive experiences. China remains important, but trade restrictions, localization requirements, and slower growth complicate the opportunity.

Tariffs also expose how misleading a country-of-origin label can be. Chips may be fabricated in Taiwan or Korea, packaged elsewhere, and assembled into devices in China, Mexico, or Southeast Asia. Duties at the final-product stage can alter competitiveness overnight. Add shipping disruptions, export controls, and currency volatility, and growth has to be judged against landed cost and supply resilience, instead of market-size figures.

Recurring Revenue Moved to the Center

Cloud signage, remote monitoring, advanced support, and managed services were separate opportunities a year ago. They're merging into one operating model. As AV real estate gets larger, more distributed, and more software-defined, customers need continuous management instead of occasional break-fix intervention.

This is where integrators can turn project revenue into contracted revenue, and where manufacturers, including NETGEAR AV, can build durable software and support economics. Ecosystem partnerships matter more too. Customers expect a single view across a mixed system, and that only happens with real interoperability.

So, what's still true? AV is becoming inseparable from the network. What changed? AI accelerated demand while tightening the component base, and geopolitics made execution more regional and more expensive.

The next year of growth will punish companies that merely sell more boxes. It will reward those that make complex, distributed AV systems open, observable, secure, and economical to run. That's a tougher opportunity than we described a year ago, but it's also a better, more sustainable business.

Executive Summary

• AV Technology's Cindy Davis shares a 30,000-foot view from her interviews with nearly 20 AV/IT industry experts on the state of AV/IT today.
• Hybrid Migration: Organizations are taking an incremental, vendor-agnostic approach to transition to networked AV/IT environments without disrupting operational continuity or replacing functional legacy hardware.
• Unified Security: AV devices are treated as core network endpoints, requiring robust authentication, encryption, and segmentation to align with broader enterprise IT security standards.
• AI & Cloud Integration: Cloud management and agentic AI are driving operational efficiency by automating routine configurations, facilitating predictive maintenance, and centralizing remote control.
• Links to all the interviews.

After nearly 20 interviews, I am sharing a 30,000-foot view of what I am hearing on the state of AV/IT.

The transition to networked AV/IT environments represents a fundamental shift in how organizations manage communication infrastructure, and industry leaders agree that wholesale replacement of existing systems is rarely the practical path forward. While manufacturers widely offer comprehensive networked suites, the primary barriers to adoption remain consistent across the industry: the necessity of maintaining operational continuity with legacy hardware that has not reached the end of its lifecycle, the complexities of integrating AV into established IT security frameworks, and the resource constraints faced by lean technical teams.

Many experts advocate for an incremental, hybrid approach that treats existing investments as assets rather than obstacles. By leveraging interoperable, vendor-agnostic platforms, organizations can integrate new IP-based technologies alongside legacy equipment, allowing for phased migration on their own schedules rather than forced infrastructure overhauls. This strategy avoids the cost and disruption of a “rip-and-replace” mentality while enabling facilities to scale capabilities as budgets and priorities allow.

Security is no longer viewed as an isolated concern but as an extension of enterprise governance. As AV devices become critical network endpoints, they must adhere to the same authentication, encryption, and segmentation standards as any other IT asset. Manufacturers emphasize that shifting AV traffic to the network offers an opportunity to bring disparate devices under a unified security umbrella, provided that planning begins with security in mind rather than as an afterthought. Many experts note that a dedicated AV network, rather than simply merging everything onto the corporate LAN is often the most effective way to balance high-bandwidth requirements with manageable risk.

AI and cloud technologies are playing pivotal roles in this transition, serving as catalysts for both efficiency and smarter operations. Cloud platforms function as the essential control plane, offering centralized visibility, remote management, and proactive diagnostics that reduce the operational lift for distributed teams. By removing the need for manual, on-site troubleshooting, cloud-native tools allow IT staff to focus on higher-level governance and strategic planning.

Artificial intelligence is evolving from a theoretical concept into a functional tool for automation and intelligence. AI is being utilized to analyze operational data, predict potential failures, and automate routine configuration tasks, reducing the “learning curve” that has historically kept some networked AV out of reach for smaller organizations. The emergence of agentic AI, capable of interpreting intent and interacting with systems through standard interfaces, is beginning to shift the operational model from manual navigation to automated, intent-based management.

The consensus among industry leaders is that the future of professional AV is not defined by the breadth of a manufacturer’s hardware portfolio, but by the intelligence of the ecosystem managing it. Success depends on open architecture and strong partner integrations that allow customers to maximize their current infrastructure investments while progressively layering on the cloud-based management and AI-driven insights that define modern enterprise environments. The goal is a transition that is additive and secure, transforming meeting spaces into intelligent data hubs where technology fades into the background, supporting consistent, high-quality collaboration without requiring constant human intervention.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Lital Grossman, Executive Director at OpenCloud AV

Most networked AV today is still siloed by manufacturer: each vendor’s devices report into their own closed cloud, their own app, their own dashboard. IT ends up managing a patchwork of parallel systems instead of one network, which recreates the exact problem networking was supposed to solve.

None of these are solved by adding another closed platform. They’re solved by a common, open layer that any device—old or new, any manufacturer—can plug into on equal terms. That’s the case for open cloud APIs: they let IT apply the same security posture and visibility to AV that it already applies to every other networked endpoint, without forcing anyone to rip out working hardware or bet on one vendor’s ecosystem.

Once that data is flowing through an open, standardized cloud layer, AI becomes practical: predictive maintenance, anomaly detection, and fewer support tickets, because the models can finally see the whole room instead of one brand’s slice of it.

This is the shift OpenAV Cloud exists to drive—not another proprietary platform, but an industry framework so networked AV works for everyone with every system and every vendor.

None of this gets fixed by another closed platform. It gets fixed by an open layer any device, from any manufacturer, can plug into on equal terms. That’s the case for open cloud APIs: one security posture, one set of tools, across every device on the network, regardless of brand or age.

Once that data flows through a common, open cloud layer, AI becomes practical—predictive maintenance, anomaly detection, fewer tickets—because it can finally see the whole room, not one manufacturer’s slice of it.

That’s what OpenAV Cloud is building toward: not another platform, but the framework that makes networked AV work as one system.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Richard Jonker, Vice President of Commercial Business Development at NETGEAR Enterprise

The promise of networked AV is compelling, but the transition doesn´t require replacing everything overnight. The biggest challenges are existing infrastructure and security, but neither is a dealbreaker. With the right network strategy, organizations can modernize at their own pace while protecting their existing investments.

Infrastructure first: AV over IP is not simply another IT application. High-bandwidth video, multicast traffic, precise QoS, and predictable latency place demands on the network that typical enterprise traffic does not. Convergence does not mean running AV on the corporate LAN. In almost all deployments, AV should operate on a dedicated network, managed using IT best practices but engineered specifically for real-time media.

Security requires the same discipline as any managed endpoint. As AV systems become connected, they need authentication, encrypted communications, access control, continuous monitoring, and regular firmware updates. A dedicated AV network does not reduce that requirement, but it makes consistent policy enforcement more practical and operational risk easier to contain.

AI and the cloud are accelerating this transition. Cloud platforms provide centralized visibility, remote management and lifecycle monitoring across distributed deployments, reducing operational overhead. Network AI builds on that foundation by finding performance anomalies, simplifying troubleshooting, predicting failures before users notice them, and, increasingly, automating routine management tasks. Together, they allow IT and AV teams to spend less time supporting systems and more time delivering reliable user experiences.

Successful AV/IT convergence is not about merging everything onto one network; it is about applying IT discipline while designing infrastructure that meets the unique requirements of professional AV.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Omer Brookstein, CEO and co-founder of XYTE

Every AV vendor now claims a comprehensive portfolio. Yet the more consequential shift is beyond AV: enterprise software is being redesigned for agentic AI. Salesforce’s Headless 360 made that direction explicit by opening data and actions to AI agents through machine-readable interfaces, without relying on a screen.

For AV/IT leaders, this reframes the strategic question. The objective is not to select the dashboard that displaces every other dashboard. It is to make a mixed estate accessible to people, enterprise systems, and agents.

That estate will not disappear. Displays, DSPs, cameras, and controllers from multiple manufacturers may retain years of useful life, making wholesale replacement economically unsound and operationally disruptive. Giving agents access also raises the security stakes. An agent observing device health presents a fundamentally different risk from one that can reboot, reconfigure, or provision equipment. Strong identity controls, least-privilege access, approval gates, and audit trails must be built into the architecture.

Cloud provides the shared data and control layer. It can standardize device data, operational history, and available actions across current and legacy systems, allowing organizations to introduce intelligence without tying progress to hardware refresh cycles.

Agentic AI then shifts the operating model from navigation to intent. Teams can ask an agent to identify devices at risk, investigate a recurring room failure, prepare rooms for high-stakes meetings, or recommend the next action. Near-term value lies not in unfettered autonomy, but in governed automation: agents diagnose issues, correlate context, and prepare remediation while people authorize higher-risk actions.

The next leaders in AV will not be distinguished by suite breadth or interface polish. They will make existing infrastructure understandable and safe for enterprise systems and AI agents to act on.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Bob Bonniol, Chief Innovation Officer at ACT Entertainment

Many productions—global broadcasts, opening ceremonies, launches watched by billions in real time—don’t get a second take. In those instances, the KPI that matters isn’t brightness or resolution; it’s uptime under nation-state-grade observation. At ACT, we call this “Tier Zero.”

When you’ve got one shot, the conversation about networked AV changes completely. Things we call barriers to entry, security, entrenched infrastructure, and equipment costs aren’t reasons to delay the transition; they are specifications the transition must meet.

Take security, for example: A networked AV system is an IT system, and it should be secured like one. That’s not a burden; it’s an upgrade. The moment video, audio, and control enter ordinary network infrastructure—ST 2110 and IPMX for video, Dante for audio, sACN for lighting—they inherit 30 years of hardened IT discipline: segmentation, authentication, and observability.

The real barrier is AV people learning to think like network engineers and network engineers learning that packet loss happens in front of an audience.

Existing infrastructure is the same story, inverted. Abandoning a working pipeline isn’t trivial, and the standards don’t ask you to do so. Open transport migrates one signal at a time. Solutions like tvONE CALICO video processors and Green Hippo Estuary media controllers already operate natively in ST 2110 environments, forming a fabric that integrates the past rather than replacing it outright.

This is where AI and the cloud stop being buzzwords and start being load-bearing. The cloud takes everything, including rendering, previsualization, and fleet monitoring, out of the building and makes a thousand-node network operable by fewer people. That isn’t a gimmick; it’s how you earn the confidence to trust a network with a one-shot event.

For decades, each discipline had its own infrastructure. Now, everything is data on a shared network. The question is no longer when to migrate; it’s which signal moves first.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Andrew Starks, Board Member and Marketing Work Group Chair at AIMS

These days, many vendors talk about offering complete suites of networked AV/IT solutions. For most organizations, however, the real question isn't whether a suite exists; it's whether adopting it means starting over. Security is often the first concern, and for good reason: Networked AV puts audio and video traffic on the same infrastructure that IT teams are already responsible for protecting. Systems that rely on proprietary approaches to identity and access control tend to create more work for IT departments, while those built around established standards for encryption and authentication integrate more easily into existing security frameworks.

Legacy equipment is another factor that’s often overlooked in these conversations. Most facilities have made significant investments in gear that still works perfectly well, and few of them can justify tearing it out on a vendor's timeline rather than their own. Phased migrations, where new IP-based systems coexist with existing equipment, give organizations more room to move at a pace that matches their budget, operational priorities, and risk tolerance.

The real value of this approach becomes even more apparent with the adoption of cloud and AI technologies. Once content moves across standard IP networks instead of dedicated point-to-point connections, distributed production, ground-to-cloud workflows, and AI-assisted capabilities like automated monitoring and quality control become far more practical. These capabilities are still maturing across the industry, but it’s already clear that the organizations best positioned to take advantage of them are those that built flexibility into their infrastructure from the outset.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Randy Dickerson, Vertical Account Manager, Broadcast, Sports, and Enterprise at Panasonic

As network AV systems become the industry standard, organizations face a common challenge: how to modernize without disrupting existing operations. A complete tech overhaul isn’t always the solution, and replacing entire ecosystems can be costly and disruptive to existing production workflows. By taking an incremental approach, broadcast teams can integrate IP-based technology alongside legacy hardware-based equipment, extending the value of existing investments and laying the foundation for future growth across network AV.

Live production and broadcast teams require flexibility and adaptability, making AVoIP ecosystems a game changer. With remote management capabilities, teams can create scalable workflows and streamline control of multiple systems from a central management hub. This enables technicians to manage live video streams, audio inputs, and preset AV assets without the need for additional hardware. For teams with existing AV infrastructure, network AV adoption doesn’t have to be all or nothing. With hybrid AVoIP and hardware-based ecosystems, teams can replace outdated equipment as needed, using network solutions to support existing systems—not overtake them. Over time, teams can adapt to operating over IP networks and use the technology to streamline their workflows. For live production and broadcast AV teams, this means saving time, simplifying workflows, and enabling scalable, large-scale operations.

With incremental tech upgrades and the adoption of AVoIP solutions, production teams are never static. Connected ecosystems can simplify software updates, incorporate emerging AI capabilities, and simplify integration with IT workflows, allowing production teams to evolve without sacrificing existing technology and operations.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Mark Plummer, Vice President and General Manager, Connected Platforms and Ecosystems at Legrand | AV

While many manufacturers are offering networked AV portfolios, significant structural roadblocks remain to truly integrated AV and IT systems. The hurdles are not limitations of the technology itself, but the challenges of integrating networked AV into established ecosystems.

Security is often cited as the tallest hurdle. AV can no longer operate on an isolated network, yet fully integrating AV endpoints into IT infrastructure introduces additional security considerations and places greater demands on AV/IT teams to vet, deploy, and maintain those devices. The right products make meeting those standards achievable.

Existing infrastructure presents a related challenge. Most legacy IT networks were not designed for multicast or high-bandwidth AVoIP streams, and modernizing them requires capital investment and close collaboration between AV integrators and IT engineers. AV product lifecycles also rarely align across a given installation. Bridging old and new through software-defined control platforms and open standards is essential to moving forward without unrealistic capital expenditure.

Cloud and AI each have a meaningful role in addressing these hurdles. The cloud serves as the operational backbone, enabling efficient monitoring, proactive management, and remote service delivery while reducing dependence on expensive on-premises hardware. The key is a secure cloud architecture with robust provisioning, patching, and access management built in. At Legrand | AV, our Unified Cloud Platform is built around exactly this foundation.

As AI matures, it will evolve into a proactive agent, monitoring ecosystems via the cloud or at the edge, flagging anomalies, anticipating service needs, and enabling intelligent device scheduling. Organizations that invest now in thoughtful infrastructure design and strategic lifecycle management will be best positioned to deliver the responsive, automated AV experiences that define what is next.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Joel Mulpeter, Senior Director of Product Marketing at Crestron

Security, existing infrastructure, and major AV equipment that hasn’t reached the end of its lifecycle are all important factors when it comes to making technology decisions to support spaces for today and the future. Security will always be a paramount consideration at the start of any project or technology decision—both now and in the long term—as these technologies extend beyond deployment decisions. Lifecycle then comes into play, as you’ll need support for those products for the entire intended life of the space. This could be anywhere from, say, three years to much longer, but often covers a term of five to eight years beyond deployment. Make-or-break considerations include ensuring one has the right certifications and security patches, and specifying solutions known for their longevity.

AI is helping people better understand their estates and security concerns as we apply these tools across facilities with many spaces. But, AI in the meeting space is also driving these decisions as people look for the latest and greatest meeting room experiences. Specifiers need to ensure people get the most out of their spaces, just as they would at their desktop.

Executive Summary

Risk of Delay: For end-user AV and IT collaboration technology managers, the primary strategic risk of artificial intelligence (AI) is inaction rather than early adoption. Delaying practical AI deployment incurs compounding opportunity costs in organizational learning and workflow transformation.

Focus on Practical Friction, Not AI Hype: Technology managers must separate speculative existential AI debates from immediate workplace challenges, applying available AI capabilities to eliminate friction in collaboration, room scheduling, and user support.

Redesign Workflows for True Transformation: Drawing on the electricity analogy, using AI merely to speed up legacy processes yields incremental efficiency, whereas redesigning workflows around AI capabilities drives fundamental organizational transformation.

Manage the Hidden Risk of Inaction: While the risks of taking action (e.g., product selection error, user rejection) are visible, the risk of waiting is invisible and compounding—costing organizations unaccumulated learning and uncaptured adaptability.

Adopt a Software-Era Foundation Strategy: Organizations must move past static hardware-era purchasing mindsets and choose adaptable cloud and software foundations today that allow continuous evolution alongside maturing AI roadmaps.

It is almost impossible in recent weeks in particular, to have a targeted conversation about a specific AI application without the baggage of much bigger conversations coming into play. Jobs. Human relevance. Safety. Societal disruption. And most recently, even existential risk to humanity itself. That’s before we even begin considering the potentially extraordinary positive capabilities on the horizon.

All those conversations, particularly the difficult ones, matter. We should all have a thoughtful voice in them.

But positive or negative, they largely concern futures that most of us cannot reliably define, let alone individually control or deliver. My worry in this moment is that we cannot allow the scale and emotion of those debates to bleed into the much smaller, but far more practical decisions about what we individually CAN actually pursue and influence with the AI capabilities already in our hands today.

Applied to an end-user AV technology manager, I think that distinction matters enormously.

Deliver Organizational Impact and Outcomes

Your immediate challenge is likely not to resolve the future of artificial intelligence. It is to improve collaboration, remove friction, support users, make better use of space and help people decide, learn and innovate more effectively. Ultimately, it is to deliver the organizational impact and outcomes that collaboration technology has always foundationally existed to serve.

So perhaps, for a moment, we should stop talking about “AI” at all.

Rather, let’s try to just discuss what work we are trying to improve. What frictions are we trying to remove? What valuable capabilities have we historically wanted, but could never justify because some traditional form of constraint made it unviable or impractical?

Only then might we ask whether any of that equation might have changed in an AI age.

Many of us have heard the analogy of AI as the new electricity, and I can’t help but keep coming back to it.

People did not transform their lives because they became enthusiastic adopters of electricity as an abstract and somewhat universally applicable technology. They adopted lighting, refrigeration, appliances, machinery and countless other applications that made useful things newly possible. In industry, simply replacing an old power source with electricity created some value. But the larger transformation came when organizations redesigned factories and workflows around what distributed electric power now enabled.

I think there is a useful lesson in that for us.

Transforming the Workflow with AI

Using AI to make yesterday's workflow faster can absolutely create value. Redesigning the workflow around what AI makes newly possible is where transformation begins.

Consider something as everyday as organizing a meeting.

Particularly in the post-COVID hybrid workplace, we have placed even more logistical work onto a meeting organizer simply trying to bring peers together in person. Having consciously and thoughtfully considered who needs to attend and why, there is huge friction in working through where people will physically be, what room is available, whether it offers the right capability, etc.—let alone what happens when things change in the interim.

Executives typically have EAs to absorb much of that effort and friction. Most of the rest of us do not. So I’m excited as platforms such as Microsoft Places are beginning to address pieces of that problem through more intelligent workforce, workplace, and collaborative workflow coordination. At first glance, the business case is obvious: save somebody ten, twenty, perhaps thirty minutes arranging and managing the logistics of a meeting.

Useful? Absolutely. And that’s primarily the focus of implementation ROI analysis at present.

But I think there is a more important opportunity that sits underneath that efficiency premise.

Every new workflow carries an adoption threshold. The value people believe they will receive has to outweigh not only the practical change effort required, but the cognitive and emotional effort of doing something differently. It’s the “Crossing the Chasm” proposition we all know. If the friction is too high, even objectively better experiences struggle to gain adoption.

Our industry has spent years responding to that reality through simplification and standardization. We reduced choices. Simplified interfaces. Removed capabilities users struggled to understand. We lowered the friction floor largely by reducing the complexity we exposed, often designing toward a lowest common denominator. A significant compromise—even if justifiable—to supporting the diversity premise that gives collaboration so much of its value.

But in this moment, I believe AI potentially gives us a different mechanism.

Intelligence Absorbs Complexity

Rather than removing capability to make an experience manageable, what if intelligence can increasingly absorb complexity on the user's behalf?

Now the meeting example becomes much more interesting.

Yes, an intelligent agent might find the time, the room and the appropriate technical capability. But what if – building upon that new more practical and tactical efficiency foundation - it can also remove enough friction from richer ways of collaborating? That truly transformative new workflow opportunities now themselves become more practical? Premises like identifying and proposing:

• Who should actually be in the room?
• What perspective or experience might be missing?
• What collaborative methodology best fits the intended outcome?
• How should the space or technology respond differently if the purpose is ideation rather than decision-making?
• And what needs to happen to turn conversation into immediate action?

We have always been capable of asking many of those questions. The problem is these are complex and difficult to manage and measure. Applying that level of thought, coordination and facilitation to every meeting would historically have required far more human effort and practical friction than the return could justify.

So most meetings never received it.

That is the equation AI can begin to change.

The transformation opportunity is not simply doing the same work with less effort. It is making valuable new work viable that the old effort equation never practically allowed us to do consistently or at scale.

Efficiency still matters. In fact, I think it may be foundational. But perhaps its greatest value is not the minutes we recover, but in the new foundations it unlocks.

Efficiency Removes Constraints. Transformation Exploits Their Absence.

If collaboration itself, rather than simply collaboration technology, is becoming an increasingly critical driver of organizational innovation and change, that distinction matters enormously. Better access to knowledge, more relevant perspectives, stronger conversations and better decisions can lead to faster learning, greater innovation, greater adaptability and ultimately competitive advantage.

Now the return has the potential to move beyond linear efficiency toward something much more compounding.

[ Check out other insightful collaboration and workplace AI articles from Byron Tarry here. ]

And that is precisely why the risk of “waiting” for bigger AI discussions to progress deserves more attention.

Here’s a different take on that concept. Our organizations and careers have largely been built around managing the visible risk of action. What if I choose the wrong product? What if the platform does not deliver? What if users reject it? What if something better arrives next year?

Those are legitimate questions.

The Risk of Doing Nothing is Always Harder to See.

There is rarely an invoice for value never discovered because we waited. No budget variance captures the capability our teams failed to develop. No project review measures learning we never accumulated, or a collaboration improvement that never had a chance to emerge.

That has always made inertia deceptively comfortable.

While we have spent decades optimising how we manage the risk of action, I think we now need to become much better at considering & managing the risk of inaction.

That does not mean becoming reckless. It means recognizing that risk management can no longer be nearly so synonymous with change avoidance.

Certainly amid an abundance of opportunity sometimes waiting will absolutely be the right answer. Some technologies will be immature. Some risks will be unacceptable. Some opportunities are simply misaligned. Some organizations simply will not yet be ready.

But waiting is not neutral.

If the opportunity we are deferring is merely a small efficiency gain, delay may carry a relatively small cost. But if that efficiency is the first unlock in a chain that enables a better workflow, better collaboration, and ultimately better organizational performance, then the opportunity cost compounds very differently.

And I believe that is where we increasingly sit as an industry.

I recently had a conversation with Sam Kennedy from NetSpeek about the strange relationship our industry has historically had with roadmaps.

In a hardware-centric world, showing customers too much of what was coming next could often create a reason not to buy what existed today. If tomorrow's product offered materially different capability, while today's hardware was largely static and might remain installed for five or seven years, waiting could be entirely rational. Roadmap conversations themselves therefore carried risk.

But I wonder whether we are carrying hardware-era buying instincts into a software-era capability model.

It’s clear that increasingly more of the future will arrive through agile software, cloud platforms, intelligence layers and services layered onto physical foundations already deployed.

That must therefore change the question. Rather than asking "What might I miss if I commit today?", perhaps we should increasingly ask, "What can I choose today to create meaningful value now while also maintaining a credible path toward what comes next?"

In This Moment of Uncertainty, You Cannot Buy the Future.

But you can choose foundations today that give you permission and confidence in a path to evolve into it.

That mindset should influence how we interrogate products, architectures, and partners. Clarity of roadmap should now be seen as an opportunity on all sides to increase confidence in today's decisions, as opposed to exposing a dead end.

This is not about predicting perfectly. It is about maintaining progression when perfect prediction is unavailable.

And that brings me back to where we started.

The current AI conversation is full of questions nobody can answer with confidence. But we cannot allow uncertainty about that future to blind us to the opportunities sitting within reach today, to the leadership we can show, the foundations we can build, and the transformational outcomes we can already begin to pursue.

This does not require us to be optimistic about every possible AI future. Nor does it require us to dismiss its risks. I think it just requires something much more practical: the discipline to separate what is speculative from what is actionable, and to focus our energy where we still have agency.

Today we CAN remove unnecessary friction. We CAN rethink workflows designed around old constraints. We CAN make decisions that preserve a path to tomorrow. And we CAN challenge ourselves as to whether fear of an unknowable future is becoming a misguided justification for preserving a status quo we already know is imperfect.

Because in this moment, standing still is also a bet.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: John Kruse, Solutions Engineering Manager at ViewSonic

The networked AV transition is real, and so are the friction points.

Most AV and IT teams agree on the destination: networked, managed, converged infrastructure with centralized visibility and operational efficiency. The goal isn't in dispute; getting there is. The barriers aren't philosophical; they're practical—and they share a common root.

AV teams are running lean. Managing distributed environments with limited staff is exactly why networked AV is appealing. Centralized visibility, remote diagnostics, and streamlined support would meaningfully change what a small team can manage. This desire isn't abstract; it's an operational necessity.

IT teams are running lean for the same reason. Standing up dedicated AV VLANs, configuring custom QoS parameters, and managing security segmentation for devices that may no longer receive firmware updates requires capacity that most IT organizations simply don't have available. The willingness is there; the bandwidth isn't.

Add the capital reality—functional equipment that doesn't justify replacement based on convergence alone—and the picture becomes clear: It's not a lack of vision, but rather a resource constraint operating from both directions simultaneously.

Cloud management and AI are beginning to change the calculus. Remote monitoring, centralized device management, and AI-assisted diagnostics reduce the operational lift once systems are online. The long-term staffing case for networked AV gets stronger every year.

However, the entry point remains the challenge. The same leanness that makes convergence desirable is what makes the transition difficult to initiate. Recognizing that tension honestly is the first step toward planning around it.

Most business leaders don't lack ideas, ambition, or potential. Their challenge is bandwidth, clarity, mastery, and follow through.

Running a business often requires operating across multiple disciplines at once. On any given day, business leaders may need to think like salespeople, project managers, recruiters, marketers, strategists, negotiators, technical experts, mentors, and financial decision-makers. In entrepreneurship, especially in small and midsize businesses, wearing many hats isn't optional. It's part of the job.

The problem is that while business leaders are expected to operate across all these areas, very few have the time to become deeply specialized in each one. There simply are not enough hours in the day to focus deeply on every area or master each discipline while also keeping the business moving forward. This is where the use of GenAI has become surprisingly valuable—not simply as a tool, but as something closer to a business associate.

The 'Someday' Substitute

Most conversations about AI tend to focus on automation, efficiency, loss of authenticity, or fear of replacement. While those discussions may have merit, they often overlook one of the most practical and transformative aspects of AI for business leaders: support, supplemental knowledge, and insight.

While business leaders may wear many hats, AI is uniquely capable of wearing them all in style. When implemented effectively, AI can serve as a mentor, coach, assistant, subject matter expert, sounding board, organizer, and execution partner. Not because it replaces people or expertise, but because it supplements and enhances the areas where many business owners struggle most: time, organization, research, analysis, and the ability to quickly shift between responsibilities.

One of the biggest benefits AI offers is the ability to tackle internal projects that might otherwise never happen. Most businesses have valuable initiatives that are repeatedly pushed aside because they are difficult to justify financially, operationally, or from a staffing perspective.

Whether it is creating operational systems, developing or implementing software tools, enhancing existing processes, refining hiring practices, evolving marketing strategies, establishing or updating a knowledge base, organizing CRM data, or writing internal standards, these projects often sit in the “important but not urgent” category indefinitely. As everyone knows, "someday" doesn't exist on a calendar.

Traditionally, solving these problems required dedicating internal resources that were already overloaded, sacrificing billable client work, or hiring outside specialists at additional cost and risk. AI helps reduce those barriers significantly. It allows projects to move from “good idea” to “valuable initiative” faster and with less friction than would otherwise be possible.

Personnel and Paperwork

Finding the right people is one of the most important and difficult responsibilities of leadership, and recruiting is an area where AI has proven extremely useful. Constructing job descriptions, evaluating applications, comparing candidates, building interview frameworks, and assessing fit all require time and consistency. AI can help organize and structure the hiring process by generating qualifying questions, analyzing responses, and creating interview guides tailored to the specific candidate and the priorities most important for a role.

AI is not making hiring decisions. Personal judgment, experience, interaction, and intuition still matter tremendously. What AI does is save time, provide consistency and organization, and help create a more thoughtful, consistent process.

AI has also proven highly effective at reviewing and evaluating contracts, proposals, and scopes of work. Many business leaders must assess legal language, identify risks, compare terms, validate expectations, and ensure alignment between what is proposed and what can realistically be delivered. AI can summarize documents, surface inconsistencies, flag areas that may require clarification, and provide an additional layer of review before agreements move forward. While it should never replace legal counsel or business judgment, it can significantly improve preparedness, reduce oversight, and help business leaders approach negotiations and decision-making with greater confidence and understanding.

One of the most valuable, and perhaps understated, aspects of AI is its ability to serve as a sounding board and brainstorming partner. Entrepreneurs are visionaries. Big ideas arise frequently but need to be vetted, processed, and defined to enable effective execution. AI provides a place to capture thoughts, explore possibilities, refine concepts, challenge assumptions, and organize ideas before they are lost in the noise of daily business operations.

It isn't a lack of importance that keeps many projects from getting started. What's holding them back is the overwhelming sense of what's involved and the effort required to get started. AI lowers that barrier and provides the confidence to turn what seems unattainable into something achievable. It helps close the gap between intention and execution.

Frictionless Support

Another important realization is that AI enhances confidence and preparedness. A reality of leadership is the constant need to operate outside a primary area of expertise and comfort zone. Business leaders frequently need to make informed decisions on subjects they may only partially understand, including operations, finance, marketing, legal language, software development, or business strategy.

AI does not replace expertise, experience, or understanding, but it dramatically shortens the distance between uncertainty and informed action. It provides context, accelerates research, surfaces key considerations, and helps business leaders ask better questions. In technical industries like AV, where platforms, APIs, products, and client expectations evolve constantly, the ability to adapt quickly has become as valuable as deep specialization.

Perhaps most importantly, AI provides something many business leaders rarely have enough of: frictionless support. There is no need to schedule a meeting, wait for availability, or worry about burdening someone with another question or idea. No matter the task, AI is immediately available.

The use of AI accelerates learning by making information, refinement, and iteration immediately accessible. It allows business leaders to develop working knowledge across more disciplines without the traditional delays of learning. As users become better at asking questions, validating information, refining prompts, and applying insights appropriately, they gain deeper understanding.

That does not mean AI is perfect or that expertise and experience no longer matter. Quite the opposite. AI still requires oversight, verification, judgment, and accountability. Human relationships, emotional intelligence, leadership, and real-world experience remain irreplaceable.

When used thoughtfully, AI can significantly expand what a small business leader or team can accomplish. It provides scalable access to knowledge and skills that once required larger teams or budgets. While some may view AI as a threat, it offers business leaders an opportunity to operate at a level once considered out of reach.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Adam Sowers, Senior Manager, Business Development at Sony Electronics

As the industry shifts toward fully networked AV/IT environments, the conversation is no longer centered on hardware alone. Cloud platforms, AI, and software-defined management are critical components of modern AV deployments, helping organizations improve efficiency, scalability, and operational visibility. However, there are still barriers to adoption that must be addressed.

Security remains the primary consideration. Any new solution must align with IT governance requirements, reduce organizational risk, and integrate into existing security frameworks. Organizations must also consider the realities of their installed base, including existing infrastructure investments, legacy systems that have not yet reached end of life, and the operational complexity of adopting new standards while maintaining business continuity.

AI is accelerating this transition by enabling greater automation, predictive analytics, intelligent troubleshooting, content management, and personalized user experiences. From virtual assistants to proactive system monitoring, AI is helping organizations maximize uptime, reduce support burdens, and improve customers’ experiences.

Cloud platforms deliver centralized management, remote visibility, and actionable insights across distributed environments. When combined with content, collaboration, and device management platforms, cloud-based solutions create more consistent, scalable, and repeatable user experiences while reducing operational complexity.

Interoperability is equally important. No organization wants to be locked into a single ecosystem. Success depends on open architecture and strong partner integrations that allow customers to leverage existing investments while adopting new capabilities at their own pace. At Sony, we believe innovation happens through partnership. We continue to work across the AV and IT ecosystem to deliver integrated, end-to-end solutions that simplify customers’ deployment and management.

The transition to networked AV/IT requires thoughtful planning, but the industry direction is clear. Organizations that prioritize security, interoperability, remote management, and operational intelligence are best positioned to modernize their environments and realize the full value of cloud and AI-enabled solutions.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Jakub Kolacz, Manager of Product Management Software at Sennheiser

Without centralized visibility into how networked audio devices are behaving across a deployment, AV and IT teams are effectively reactive. Problems surface when users report them—not before. That dynamic is what cloud-based device management is designed to change, and it is where the most meaningful progress in networked audio is happening right now.

When every device across every room and every campus reports into a unified, browser-accessible interface, AV and IT teams gain a shared, real-time view of the entire environment. Firmware alignment can be maintained consistently without technician dispatch. Anomalies can be identified and addressed before they affect a meeting or a class, and configuration changes can be applied at scale rather than room by room. For organizations managing distributed deployments across multiple buildings or campuses, that kind of oversight should be viewed as an operational requirement rather than a convenience.

The longer-term case for cloud management is what these platforms become over time. As they accumulate operational data across deployments, they create the foundation for AI-driven capabilities that can shift teams from reactive troubleshooting toward proactive management. Routine diagnostics, firmware validation, and performance monitoring can move from manual processes toward automated workflows, allowing AV and IT staff to focus on governance and exception handling rather than break-fix cycles.

Critically, none of this requires replacing equipment that still has useful life. Cloud visibility functions as a connective layer above existing infrastructure, allowing organizations to modernize their operational approach without forcing a hardware refresh cycle. That makes the transition financially realistic for a much broader range of organizations and allows migration to happen at a pace that fits both budget and risk tolerance.

Meet swXtch.io's AI-based broadcast engineer, better known as abbe. The agentic platform was designed to remove the infrastructure and networking complexity behind live media workflows.

[A Turning Point for AI]

“The AI models are becoming incredibly capable but putting them into a live production still requires expertise across networking, cloud infrastructure, and AI software,” said Brent Yates, CEO of swXtch.io. “abbe is designed to remove that complexity. You describe what you want to accomplish, and abbe stands up everything needed to make it work. And because workflows are not locked to one model, you can easily optimize it as the technology changes. abbe simplifies AI for live media.”

abbe removes the requirement for operators to configure networks, cloud infrastructure, compute resources, and AI software in media routing and interface workflows. abbe takes a conversational description of the desired outcome and deploys the necessary infrastructure, networking, and software required to make the workflow run and does so in the most economical way while meeting performance requirements.

abbe is a cloud-agnostic orchestration layer, able to deploy live media and AI workflows across any provider including Microsoft Azure, Oracle Cloud Infrastructure (OCI), and Amazon Web Services (AWS). Workloads are located based on user requirements including optimizations for cost and latency, without forcing the operator to design a different solution for each cloud environment.

For live media networking, abbe provides SRT management and control, enabling operators to ingest, monitor and distribute streams globally without manually configuring the underlying infrastructure. abbe is designed to automate decisions around where and how live media moves, helping operators maintain reliable, high-quality feeds while reducing the manual intervention traditionally required to respond to changing network conditions.

For AI workflows abbe will demonstrate a live audio processing workflows using NVIDIA models and other select partners. An operator can describe the desired outcome and abbe stands up the cloud infrastructure, networking, security, and software required for the audio processing use case.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Sanjay Kulkarni, Vice President of Product at QSC

The convergence of AV and IT is now an operational reality for most organisations. Networked AV architectures offer clear benefits in scalability, manageability and data-driven decision-making, but adoption is rarely as simple as replacing existing systems.

The biggest barriers are often organisational, financial and operational considerations, rather than technical capabilities. Existing AV investments often remain functional and valuable, making upgrades difficult to justify. Security, governance and interoperability have become priorities. As AV systems connect to enterprise networks, they must meet the same standards as any other IT asset.

The most successful transitions are incremental rather than disruptive. Organizations want to modernise at their own pace, extending the life of existing infrastructure while moving toward interoperable, software-centric environments. This shift is driving interest in full-stack AV platforms that bring together devices, software and cloud-based management within a single ecosystem.”

Cloud technologies are accelerating this shift by providing centralised visibility, management and analytics across geographically dispersed spaces. Instead of managing rooms and devices as isolated systems, enterprises can gain a holistic view of performance, utilisation and user experience across their technology estate.

Beyond automating routine administrative tasks, AI technologies can help organizations harness real-time data to improve visibility, generate actionable insights, and support more informed decision-making across connected environments.

At Q-SYS, we’re seeing organisations prioritise flexible, software-centric architectures that help them extend existing investments while creating a path to cloud-enabled management, data-driven insight and evolving intelligent technologies. The same thinking sits behind the high-performance workplace discussion, as AV environments increasingly need to be adaptable, connected and easier to manage over time. Ultimately, the future of AV/IT will be shaped by secure, intelligent ecosystems that can evolve with changing workplace needs.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Joe Andrulis, Executive Vice President of Corporate Development at Biamp

The big shift we are seeing as an AV manufacturer relates to how AV solutions are increasingly software-defined. In other words, the days of purpose-built, hardware-heavy systems that required on-site expertise to reconfigure are giving way to software-defined environments where organizations can adapt their AV infrastructure to meet changing needs without touching a rack.

This shift has fundamentally changed the technology requirements for practically all types of environments. Spaces that previously might have only required microphones, loudspeakers, and a projector must now often seamlessly support conferencing platforms, high-quality audio capture, video distribution, and remote collaboration. The result is a growing convergence of technologies that were once managed separately.

To get there, organizations must look at platforms that can bring together digital signal processing, conferencing, room control, amplification, and audio networking within a single ecosystem—often accessed through the cloud.

Control plays a big part in this paradigm shift. Historically, powerful AV control systems came with equally heavy programming requirements, putting them out of reach for organizations without dedicated technical staff. Rather, the shift toward intuitive, no-code platforms means internal teams can now deploy sophisticated automation that end users can manage day-to-day, without ongoing support.

AI is another factor driving this shift. AV systems with embedded AI can respond to the environment automatically, including changes in usage patterns that previously required lots of planning or forethought. These intelligent tools can now continuously adapt to environmental fluctuations, ensuring a smoother and more refined user experience across diverse scenarios.

At the end of the day, this software-defined AV infrastructure is enabling hardware to consolidate, last longer, and provide a greater experience for everyone along the AV value chain.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Petro Shimonishi, Director at Panasonic Projector & Display Americas

Many of today’s production teams across entertainment venues, higher ed, and corporate settings are making the transition to networked AV—but few can justify replacing hardware-based equipment that’s still functioning. Thankfully, a hybrid strategy has emerged, giving AV teams the flexibility to modernize outdated solutions while maintaining existing legacy equipment under one ecosystem.

This happens as the AV industry hits an inflection point: Customers are no longer buying isolated projectors and displays, but are instead investing in connected visual communication platforms. Remote management, interoperability, and real-time operational data have become expectations, and network connectivity now carries IT-grade security requirements, including zero-trust architecture, role-based access, and encrypted signal paths. AI and cloud services are moving past buzzword status too: Predictive maintenance, automatic camera framing, and content intelligence are already easing the load on stretched AV/IT teams, with cloud-to-cloud connectivity letting organizations add these capabilities gradually rather than all at once.

At Panasonic Projector & Display Americas, our goal is to empower innovation without disruption, ensuring AV and IT teams can integrate networked solutions without sacrificing critical time and resources. As modern AV and IT teams continue to work together, we aim to enable integrators to evolve in accordance with their organization’s needs and goals. This means building open APIs and standards-based integration that let AV/IT teams evolve at their own pace, deploying AI and cloud services only where they create measurable value while protecting the equipment already in place. The future of professional AV is not defined by replacing every device on the network; it centers on creating secure, intelligent ecosystems that allow organizations to modernize at their own pace.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Yannic Laleeuwe, Marketing Director, Meeting Experience at Barco ClickShare

For years, AV and IT leaders have focused on integration. The priority was to connect devices, platforms, and spaces into one coherent environment. In many organizations, that foundation is now largely in place. The next challenge is making meeting rooms intelligent enough to support AI-driven collaboration.

Hybrid work has reshaped expectations. People move between home, office, and travel, expecting meeting experiences to move with them. But many meeting spaces still rely on fixed setups and fragmented technology that slow people down rather than support them.

At the same time, collaboration platforms continue to evolve. AI is already embedded into daily workflows, helping teams capture decisions, generate insights, and stay aligned. In Microsoft Teams, for example, Copilot can use meeting speech-to-text and transcription data to surface discussion points, summarize conversations, and suggest follow-up actions. These experiences, however, are only as good as the meeting input behind them. Garbled audio, a camera that misses half the room, or a five-minute scramble to connect a laptop don’t just frustrate people in the meeting; they also degrade the transcript Copilot is working from.

This is where AV/IT is being redefined. It is no longer only about connecting hardware; it is about enabling collaboration that is simple enough that people use it without thinking, and consistent enough that AI can trust what it captures. Simplicity, interoperability, and security are expectations. As technology fades into the background, the focus shifts to uptime, room visibility, performance, and the quality of the meeting experience itself.

The meeting room is no longer just a place where work happens; it is where the quality of collaboration begins. When that experience is easy to start, reliable, and inclusive, it gives AI the right foundation to deliver real value across platforms like Microsoft Teams and Copilot. The organizations that move early will not just run better meetings; they will build smarter ways of working across the entire business.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Jonathan Mangall, Managing Director, EMEA at Utelogy

At Utelogy, we’re seeing a fundamental shift in how organizations approach AV. The conversation has moved beyond deploying technology to managing it as part of the wider enterprise IT ecosystem. Networked AV, cloud technologies, and AI are transforming operations, but successful adoption depends on helping organizations evolve without disrupting the investments they've already made.

Legacy infrastructure remains a key challenge. Most organizations operate multi-vendor AV environments with years of useful life remaining, making rip-and-replace impractical and cost-prohibitive. That's why Utelogy champions an open, vendor-agnostic platform that unifies, monitors, and manages existing AV while protecting previous capital investments.

Security is equally critical. As AV devices become enterprise network endpoints, they must meet the same governance, authentication, and compliance standards as every other connected IT asset. Utelogy’s enterprise-grade security and integration with existing IT workflows are fundamental to ensuring AV can be managed with the same confidence as the rest of the technology estate.

Cloud is accelerating this transformation by providing centralized visibility, remote management, and the scalability needed to support global deployments. Whether organizations choose cloud, hybrid, or on-premises, flexibility is essential to meet operational and regulatory requirements.

AI is now taking enterprise AV management to the next level. We see AI as an enabler rather than a replacement for IT teams. By analyzing operational data, identifying anomalies, predicting potential issues, and automating routine tasks, AI allows organizations to move from reactive support to proactive, intelligent operations that improve user experiences while reducing operational overhead.

The future of AV/IT isn't defined by the hardware, but by how intelligently it's managed. By combining open integration, cloud-native management, and AI-driven automation, Utelogy helps customers maximize current investments while preparing for autonomous AV operations.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Josh Blalock, Global Director, Alliances & Engagement at Shure

The conversation around AI has matured. A year ago, everyone was talking about AI theoretically. Today, the real question is whether the infrastructure underneath it is actually ready to support the outcomes organizations expect, and if their AI roadmap matches their business roadmap.

As more companies rely on AI to summarize meetings, assign actions, automate workflows, and collaborate with agents, good enough isn’t good enough anymore. Every meeting is creating data that those systems depend on. If the audio isn’t captured accurately or your collaboration environment is fragmented across disconnected platforms, those small gaps become much bigger problems once AI agents start making decisions from that information.

Organizations shouldn’t think about meeting rooms as just places where conversations happen; they should be thought of as spaces where business data is generated, and decisions are taken. The same way organizations wouldn’t accept missing records in CRM or gaps in email history, the same should apply to incomplete or inaccurate meeting data.

The cloud plays a critical role by giving IT teams centralized visibility and management across their collaboration environments, while AI unlocks new ways to turn meeting content into action.

But neither delivers value without a strong foundation. The organizations that will benefit most are those that build an ecosystem that captures the highest-quality data from the very beginning. That’s what enables AI to deliver meaningful business outcomes.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Wylie Dunham, Senior Network Engineer and AVoIP Product Manager at Atlona

The continued growth of uncompressed AVoIP technologies such as SDVoE, along with many upcoming IPMX implementations, is placing greater emphasis on multi-gigabit network infrastructure. These technologies deliver high image quality, ultra-low latency, and predictable performance, making them ideal for demanding applications. However, many implementations also rely on 10GbE connectivity at the edge and higher-capacity network uplinks. For many organizations, the challenge is no longer the AV technology itself, but the cost and complexity of extending high-bandwidth network infrastructure to every endpoint.

At the same time, enterprise network investments are being driven by priorities well beyond AV. Wi-Fi 6E and Wi-Fi 7 access points, cloud services, and increasing user density continue to shape infrastructure planning and budgeting. While MultiGig switching is becoming more common, it is typically deployed where those demands exist, with most access ports throughout the enterprise still operating at 1GbE. As a result, AV projects must increasingly align with existing IT strategies rather than expecting networks to be redesigned around video distribution. When these technologies are deployed, they are often isolated, not leveraging the AV everywhere feature of networked AV due to capacity requirements from the network edge through the core.

This raises an important question for the industry: Does every deployment require an uncompressed 10Gb stream? Answers depend entirely on the application. Mission-critical environments such as command and control, medical visualization, and live production may justify the investment in uncompressed transport. Meeting rooms, classrooms, digital signage, hospitality, and corporate communications often have different priorities, where scalability, infrastructure efficiency, and total cost of ownership can edge out the need for absolute minimum latency. As AVoIP continues to evolve, selecting the right transport technology should be driven by application requirements—not the assumption that every deployment demands the highest-available-bandwidth solution.

AVT Question: Please share insights on the ongoing transition to networked AV and the role the cloud and AI play.

Thought Leader: Steven Barlow, President of DVIGear

Every vendor claims a full networked AV/IT suite. The real question is, how do you get there without ripping out equipment that still has years of life left, and without opening new security holes? The ideal approach is a transition that's additive rather than wholesale. DisplayNet uses standards-based, uncompressed distribution that can run over the IP network you already operate, coexisting with the matrix switchers and endpoints already in place—so you can migrate on your own schedule instead of someone else's, extending the infrastructure you own rather than replacing it.

On security, putting AV on IP isn't a new attack surface to fear; it's the opportunity to bring AV under the same enterprise governance—segmentation, authentication, monitoring—that already protects everything else. Uncompressed, deterministic signals stay on premises where real-time video belongs. That also defines the cloud's role: Latency keeps the pixels local, so the cloud handles the control plane of orchestration, monitoring, and configuration.

The most stubborn barrier has always been expertise. Operating AV-over-IP has meant mastering proprietary APIs and control syntax. DisplayNet Connect for AI Agents removes that bottleneck. As the first AV-over-IP system with native Model Context Protocol support, it's directly controllable by Claude, OpenAI Codex, Gemini CLI, or any MCP-compatible agent. A technology manager states intent in plain language and the system configures itself, compressing what once took days of custom development into minutes.

The winning transition is incremental, secures itself with the IT stack you already trust, and uses AI to erase the learning curve that kept networked AV out of reach.

Almost 20 years ago, when I was deeply invested in the sustainability proposition and the emerging world of green building, I read a book with a title that is difficult to ignore for anyone in the AV integration space: Broken Buildings, Busted Budgets.

Written by Barry LePatner, the book examined why construction projects so often produced familiar poor outcomes: cost overruns, delays, disputes, compromised results, and frustrated owners. Sound familiar?

The book was published in 2007, long before the current AI moment, and certainly was not about hybrid work, intelligent buildings, adaptive collaboration environments, or the future of the modern workplace.

Yet what it triggered in me at the time has stayed with me since, and feels even more relevant today. The way we go about building something is as important as the thing we intend to build.

When a process is fragmented, information is incomplete, incentives are misaligned, and accountability is divided, disappointing outcomes should not always be treated as isolated failures. They may actually be the predictable product of the system used to create them.

That principle has particular relevance for the AV and collaboration industry because we have long occupied an unusual position between two worlds. Our value is increasingly shaped by the digital environment: software, platforms, data, user experience, and now intelligence. Yet our systems and delivery model remain highly embedded within the physical environment, dependent upon walls, ceilings, furniture, cabling, acoustics, lighting, power, and construction schedules.

Despite years of discussion about AV and IT convergence, the physical side of that equation has continued to dominate how our environments are delivered. AV is still largely funded, designed, procured, installed, commissioned, and handed over through workflows inherited from a project-centric construction model.

That model was/is not designed around the continuous adaptability, shared outcomes, and ongoing learning realities of today. It was designed to define what largely static physical structures would be built, divide that answer into scopes, allocate risk, control change, and eventually reach completion. Because AV was so closely integrated into that process, we inherited much of the same inertia, fragmentation, and accountability challenges.

Interconnected Environments

As collaboration outcomes become more dependent on the speed and agility of digital capability, what was once an awkward tension risks becoming a foundational constraint.

The workplace is becoming one interconnected environment, whether our organizational structures are ready for it or not. Physical space, workplace applications, collaboration platforms, occupancy data, identity, employee experience, organizational policy, and eventually AI-enabled contextual intelligence are all becoming increasingly interdependent.

That means more stakeholders in the build process, greater consequence to the decisions each makes, more complexity across the lifecycle, and much less certainty about what future users and workflows will require.

In other words, we are taking a delivery model that was already struggling with fragmentation, information asymmetry, and divided accountability, then asking it to absorb more participants, faster change, greater integration, and far less visibility into the future.

The book does not provide a contemporary blueprint for solving that challenge. But it offers a valuable diagnosis of the familiar model we still work within, and an invitation to recognize why simply forcing more technology and complexity into it will not produce a fundamentally different outcome.

That is why the traditional reliance on defining project-centric scope upfront deserves much greater scrutiny.

Rethinking Scope

Our procurement models typically begin by trying to define the answer. Requirements are established, translated into specifications, divided between disciplines, priced, contracted, and then managed against the original definition. Commercial accountability depends upon the assumption that the intended result can be understood with enough confidence at the beginning.

For physical construction, much of that discipline will always be necessary. Buildings require plans, budgets, sequencing, code compliance, and contractual clarity.

But the modern workplace presents a different challenge. Organizations are still being asked to define long-term requirements when their visibility into future need is shrinking. AI is changing interfaces, workflows, support models, collaboration patterns, and the role of the workplace itself. Capabilities that might seem experimental if not futuristic when a project begins may become commonplace before the initial deployment reaches completion.

The more intelligent and adaptive the workplace becomes, the less credible it is to believe that all meaningful value can be specified at the outset.

That does not mean scope disappears. It means scope cannot continue to be treated as a complete and static answer.

A tightly defined scope may provide immediate commercial certainty while simultaneously constraining future opportunity. It can reward delivery of what was understood yesterday while leaving no one responsible for what becomes possible tomorrow. The conventional process seeks to eliminate uncertainty, yet the future workplace must embrace the opportunity of uncertainty and a capacity to learn and adapt to whatever the future holds.

There are no quick or easy answers to this new reality. But I believe there are two practical directions end-user leaders can begin pursuing today: reconsider how the workplace itself is designed, and challenge whether the procurement and accountability models around it are capable of supporting that design.

A Layered Approach to Design

The first direction begins with recognizing that the workplace is not a single system operating to a single lifecycle. It is an interconnected environment spanning infrastructure, hardware, digital capability, and contextual intelligence. Each layer changes at a different speed and should be considered accordingly.

The infrastructure layer includes the structure, power, pathways, network cabling, acoustics, mounting provisions, furniture, environmental systems, and other relatively permanent characteristics of the space. It moves slowly, lasts a long time, and is disruptive and expensive to change. Its role should be to provide a resilient foundation without unnecessarily predetermining what must sit above it.

The hardware layer includes cameras, microphones, displays, loudspeakers, sensors, control devices, local compute, networking equipment, and other physical technology endpoints. Hardware may be digitally upgradeable, but it remains constrained by its processing power, memory, optics, connectivity, inputs, outputs, sensors, and physical architecture.

The digital layer is the software and data environment that activates and connects that hardware. It includes operating software, collaboration platforms, applications, control logic, identity, APIs, integrations, analytics, cloud services, and management platforms. This is where capability becomes far more agile, but only to the extent that the infrastructure and hardware beneath it allow.

Finally, the emerging contextual intelligence layer interprets who is gathering, why they are gathering, what they are trying to achieve, what has happened previously, which constraints or preferences matter, and how the environment might respond. It connects real-time signals, organizational knowledge, history, individual needs, and human purpose to create a more relevant and adaptive experience.

The practical principle is that each slower-moving layer should create permission for the faster-moving layer above it to evolve, rather than predetermining its limits.

That offers end-user leaders a different way to think about scope today. Does the largely static infrastructure simply support the current equipment list, or does it preserve future flexibility? Does the hardware only meet today’s specification, or can it support new software capabilities as they emerge? Is the digital architecture open and integrated enough to enable future intelligence? Are we imagining contextual experiences while making foundational decisions that may prevent them?

These are not abstract future questions. They belong in current design and governance conversations.

Moving Toward Shared Accountability

But layered design alone is not enough. A workplace may be architected for evolution and still be pulled back toward a static answer by the procurement model through which it is delivered.

That is the second practical direction for change.

A process built around tightly defined upfront scope, fragmented contracts, lowest initial cost, and responsibility that largely ends at handover will naturally reinforce the very outcomes we are trying to move beyond. It encourages each participant to optimize their own deliverable, even when the employee ultimately experiences the result as one integrated workplace.

Specification accountability remains necessary, but it is no longer sufficient. The future workplace requires greater shared accountability for how the combined environment performs, adapts, and creates value across its lifecycle.

That does not mean every partner can guarantee every workplace outcome. Collaboration quality, employee behaviour, organizational culture, and business performance will never sit entirely within the control of an architect, consultant, integrator, or technology provider.

But partners can be held accountable for their contribution to those outcomes. They can help establish the original assumptions, identify how their decisions enable or constrain the intended experience, remain involved in measuring performance, and participate in refining the environment as needs and capabilities change.

That is very different from completing a project, signing off the scope, and transferring responsibility to an operational team. It treats the workplace not as a static collection of assets, but as an organizational capability that should improve over time.

Many AV and workplace technology leaders may reasonably feel they have limited authority over these wider processes. Construction may sit with real estate. Procurement may be centralized. Workplace policy may belong to HR. AI governance may reside elsewhere in the enterprise.

But leadership has rarely been defined by remaining comfortably within an established lane. It often begins with recognizing that the existing lanes no longer serve an outcome for which you carry some responsibility.

Catalyzing Integrated Processes

This is not about AV leaders claiming ownership of the entire workplace. It is about becoming catalysts for a more integrated process: connecting physical decisions to future digital consequences, bringing the right stakeholders together before major constraints are locked in, and asking how success will be judged across the lifecycle rather than only at commissioning.

It means pursuing two connected propositions.

Design the workplace for evolution.

Procure the partnerships and accountability that allow it to evolve.

Broken Buildings, Busted Budgets was a catalyst for this reflection because it challenged the idea that flawed outcomes are always caused by the failure of individual participants. Sometimes capable people working within a flawed structure will continue to produce flawed outcomes.

For the collaboration industry, that is not only a lesson from the past. It is a warning about the future.

We cannot seek to procure tomorrow’s intelligent workplace through yesterday’s construction workflow.

We may not yet know the specific technologies, capabilities, or experiences that will define that future. But we do not need to wait for those answers before beginning the work. The practical path available today is to rethink the foundations we design and the models through which we procure, operate, and remain accountable for them, so that future change becomes something the workplace is prepared to embrace rather than something it is structured to resist.