Managing AV and collaboration technology across hospitals, clinics, classrooms, and event spaces is no small task, and for Justin Scord, Senior Manager, Collaboration & Media Services at Stanford Medicine, the challenge isn't just keeping the lights on. It's knowing where to start.
"There's always so much change, so much technology, so many different manufacturers," Scord told UC Today at InfoComm 2026 in Las Vegas. "Keeping that North Star and making sure we're building systems that are scalable and supportable is really our focus."
Scord oversees a broad footprint at the Palo Alto-based academic/medical ecosystem – from patient rooms and conference spaces to live event broadcasts. If there's a screen, a microphone, or a speaker involved, his team has a hand in it.
That sprawling remit gives him a sharp perspective on where the industry is heading.
On AI, he's optimistic – but rigorous. "I'm all about the data," he said.
Stanford's in-house data science team actively researches which AI models perform best for specific workflows, and Scord believes the wider AV industry should be asking the same hard questions.
"Ask the manufacturers where they got the research and data to choose the models they're using. That alone is going to weed out a lot of manufacturers."
His concern is that too many AI deployments are driven by commercial partnerships rather than genuine fit. "If they're not choosing the right models based on workflow and using data to show it's actually going to provide ROI, it's probably not something you want to pursue."
At InfoComm, Scord spoke about agentic AI and its potential to augment – not replace – project teams. His message was clear: AI should aggregate data, surface actionable insights, and make day-to-day work more manageable, without diminishing the people doing it.
"Get educated around machine learning and AI at a high level," he said. "Understand the limitations, and start slowly incorporating it into your workplace."
