WWT at DDAC 2026: Building the Intelligent Venue

The 2026 Disney Data & Analytics Conference (DDAC) brought together business professionals, data practitioners and industry leaders to explore how data and analytics are shaping the future of business.

For World Wide Technology, the conference provided an opportunity to take that conversation beyond traditional dashboards and analytics and into the physical world.

Our focus was the intelligent venue and a broader question: What happens when physical environments become sources of real-time, actionable data?

Modern entertainment venues already have enormous technology footprints. Cameras monitor concourses. Ticketing systems capture arrivals. Point-of-sale systems record transactions. Building systems monitor facilities and access. Years of operational data sit behind all of them.

The challenge is not necessarily collecting another signal. It is getting those signals to work together.

That idea anchored WWT's presence at DDAC 2026 and our work alongside NVIDIA to explore how data, AI, digital twins and infrastructure can come together to create environments that sense, understand, act and continuously get smarter.

WWT at DDAC: Bringing intelligence into the venue

As a Gold Sponsor of DDAC 2026, WWT brought thought leadership and hands-on demonstrations to the conference through two breakout sessions and an interactive booth experience.

Drew Pikey, Executive AI Innovation Advisor at WWT, introduced the vision through "The Intelligent Venue: From Pixels to Predictions," exploring what happens when a venue begins operating as an intelligent ecosystem rather than a collection of disconnected systems.

Kyle Lindsey, Executive AI Innovation Advisor at WWT, followed with "The Architecture of an Intelligent Venue," taking the concept deeper into the data, governance, infrastructure and operating model required to bring that vision to life.

At the booth, attendees could see these ideas come to life through spatial intelligence demonstrations, NVIDIA video search and summarization, and digital twins of Energizer Park and a modular AI factory.

Together, the sessions and demonstrations told one connected story:

Sense. Understand. Act. Compound.

Drew Pikey: From pixels to predictions

Drew's session began with a shift in how we think about venues.

For more than a century, stadiums and arenas have largely operated around the same basic model: physical infrastructure supporting scheduled events. AI, spatial computing and connected infrastructure create an opportunity to rethink that model.

Instead of disconnected systems monitored by people who react after guests experience a problem, the intelligent venue creates one living model of the environment. Cameras, sensors, turnstiles, registers and other systems contribute to an intelligence layer designed to help operators understand what is happening, anticipate what could happen next and determine how to respond.

The model follows four core steps:

• Sense: Turn signals from cameras, sensors, robots and systems into a machine-readable picture.
• Understand: Combine those signals with models and digital twins to diagnose current conditions and anticipate what could happen next.
• Act: Connect intelligence with people, software, robots and building systems so the venue can respond.
• Compound: Learn from every event so the environment begins the next one with greater intelligence.

The goal is not another disconnected AI feature. It is an architecture capable of increasing the value of the data and infrastructure organizations already own.

Kyle Lindsey: Building the architecture behind the experience

If Drew's session explored the potential of an intelligent venue, Kyle's session focused on what it takes to deliver one.

The starting point was simple: venues do not necessarily have a sensing problem.

Many already have cameras, LiDAR, access control, ticketing, point-of-sale systems, building systems and years of operational data. What may be missing is a common architecture and data foundation capable of making that environment machine-readable.

As Kyle put it:

Kyle's session emphasized what sits underneath the experiences everyone wants to see: data readiness, governance and privacy, security and architecture, and operating models.

Those elements may be less visible than an AI demonstration, but they determine whether that demonstration can become part of production operations.

"Everything above this rung is visible in a demo. Everything on it is invisible until production."

For the data and analytics community, that puts data at the heart of the intelligent venue. Before AI can drive action, signals need structure. Systems need a shared foundation. Organizations need to determine what information is captured, retained and queried. Operators also need an operating model they trust.

The AI model may generate the headline. The data foundation makes the headline possible.

Energizer Park: From digital twin to intelligent venue

To bring the architecture to life, Kyle used a WWT proof point close to home: Energizer Park, home of St. Louis CITY SC.

Built by WWT in partnership with Another Reality Studio, the digital twin represents the 22,423-seat stadium and its surrounding district. The digital twin runs on NVIDIA DGX Spark™, and Kyle's presentation paired it with a designed reference architecture incorporating NVIDIA Metropolis for vision AI agents, RAPIDS for analytics, and NVIDIA Omniverse libraries for the twin layer.

The example illustrates how information from traditionally separate systems can contribute to a common operational picture.

Imagine a camera detecting increasing density around a gate. Processing at the edge turns that signal into a structured event while the footage stays local. Ticketing, point-of-sale and access-control data can provide additional context around the same location.

Instead of operators looking across multiple systems to determine what is happening, the architecture is designed around a shared representation of the environment. Over time, governed events can create the foundation for identifying recurring patterns and improving future operations.

The principle behind the architecture is straightforward:

"Events move. Footage does not."

This approach positions privacy and governance within the architecture rather than treating them as considerations to solve after an AI application has been developed.

The digital twin also demonstrates how organizations can explore the connection between physical environments and the data needed to understand them, creating a foundation for testing how intelligent venue use cases could evolve.

Applying intelligence to the AI factory

The second use case took the framework beneath the venue and into the infrastructure powering AI itself.

In collaboration with Another Reality Studio, WWT created a completed digital twin of a modular AI factory. Kyle Lindsey used the digital twin to demonstrate how Sense, Understand, Act and Compound can extend to the infrastructure underneath the intelligent venue.

For an AI factory, sensing can include temperature, power draw, airflow and door state. Those signals can contribute to a unified model of the environment and, over time, help inform how infrastructure is operated and planned.

The connection matters because intelligent experiences ultimately depend on physical infrastructure.

As organizations move from AI experimentation toward production, determining where workloads should run becomes increasingly important. The conversation expands beyond the model itself into compute, networking, power, cooling, security and the data supporting the use case.

Data governance and protection are also important considerations. Organizations need to account for how critical and proprietary data is governed and protected, not simply where compute resides.

The takeaway is not that every organization needs the same AI infrastructure. Instead, infrastructure decisions should begin with the use case and work backward into the architecture required to support it.

Making the story real at the WWT booth

The WWT booth connected these concepts with technologies attendees could experience firsthand.

One demonstration used off-the-shelf network cameras and edge infrastructure to transform camera feeds into a top-down model of the booth. Rather than simply displaying video, the demonstration created a live map and surfaced signals such as counts, dwell and traffic by zone.

Another showcased NVIDIA Video Search and Summarization running on a NVIDIA DGX Spark™ using St. Louis CITY SC match footage from Energizer Park. Attendees could ask questions of recorded video in natural language and retrieve relevant clips and summaries.

Together, the demonstrations captured two possibilities:

One showed a venue that can see. The other showed a venue you can ask.

More importantly, they reinforced that the camera is only the beginning. The opportunity comes from turning physical signals into trustworthy data and connecting that data to how an organization operates.

What does this mean for customers?

Several themes from DDAC stood out for organizations considering how to move AI into physical environments.

• Start with what you already own. Organizations may already have much of the sensing infrastructure required to begin. Before adding more technology, understand how existing cameras, sensors, operational systems and data could support new use cases.
• Treat the data foundation as part of the AI strategy. AI is only as useful as the information underneath it. Data needs to be structured, governed and accessible. The foundation may not be the most visible part of an AI initiative, but it is among the most important.
• Design privacy and governance into the architecture. Decisions about what information is captured, retained and queried should be addressed at the data and architecture layer, not retrofitted later.
• Let the use case drive the infrastructure. AI factory conversations should begin with the business outcome. From there, organizations can determine where workloads should run and what compute, networking, power, cooling and security capabilities are required.
• Look beyond the proof of concept.

 A successful demonstration proves something is technically possible. Production introduces questions around integration, data readiness, governance, security, infrastructure and adoption. Those considerations need to be part of the strategy from the beginning.

What we're bringing back from DDAC

DDAC reinforced a theme we have seen throughout 2026: the AI conversation is moving beyond what is possible and toward what organizations can operationalize.

At DDAC, that conversation extended directly into the physical world.

Venues already generate enormous amounts of information. Cameras, sensors, ticketing systems, point-of-sale platforms and building technologies create signals about how environments operate. The next opportunity is connecting those signals through an architecture capable of transforming them into governed data, shared intelligence and meaningful action.

And the opportunity extends beyond stadiums and entertainment venues.

The same questions apply as organizations consider intelligent facilities, AI factories and other environments where digital intelligence increasingly intersects with physical operations.

For customers, that means starting with the business problem, understanding the assets and data already available, and proving how the complete architecture behaves before attempting to scale.

WWT can help bring those layers together, connecting data, AI and infrastructure with technology partners such as NVIDIA while helping organizations explore, test and validate new approaches.

Kyle closed his DDAC session with a message that captures our biggest takeaway from the week:

Ready to explore what's possible?

Ready to explore what an intelligent environment could look like for your organization? Start with the infrastructure, data and use cases you already have, and work with WWT to identify where intelligence can create the greatest impact.