What does it really take to turn AI from a flashy experiment into something that creates measurable business value?

In this episode of Tech Talks Daily, I sat down with Angela Virtu from American University's Kogod School of Business to talk about what business leaders should actually be paying attention to as AI moves into a new phase in 2026. This conversation goes far beyond the usual headlines about bigger models and faster tools.

Angela brings a rare mix of academic leadership and hands-on startup experience, which means she understands both the technical side of AI and the hard business questions around adoption, trust, and ROI.

One of the most interesting parts of our discussion centered on how American University's Kogod School of Business became one of the first AI-first business schools. Angela shared how that shift was never really about chasing hype. It was about recognizing a real change in the workplace and preparing students for jobs, workflows, and expectations that are already being shaped by AI.

From faculty training to culture change, she explained how transformation only works when leadership is willing to support experimentation and accept that some ideas will fail before the right ones take hold.

We also spent time unpacking where businesses stand right now in the AI adoption cycle. After years of pilots and proof-of-concept projects, many companies are under pressure to show results. Angela offered a refreshingly honest take on why so many AI projects stall and why adoption alone is a weak metric. Instead, she argued that companies need to tie AI initiatives to clear business problems and existing KPIs. Whether that means customer support resolution times, employee productivity, or operational efficiency, the point is simple. AI needs to earn its place.

Another thread running through this episode is governance. As AI becomes more deeply embedded inside organizations, the conversation is shifting toward oversight, accountability, and trust.

Angela explains why the strongest governance models are often shared across the company rather than locked inside one team. She also discusses the need for closed systems, stronger communication, and honest disclosure when businesses use AI in customer-facing environments. That part of the conversation feels especially timely as more brands try to balance innovation with customer expectations.

We also looked ahead at what is coming next, from model orchestration and vertical AI to the rise of physical world models and even the possibility of AI agents becoming a customer audience in their own right. It is one of those episodes that will give business leaders, technologists, educators, and curious listeners plenty to think about.

If you are trying to understand where AI strategy is headed in 2026, and how to separate real value from noise, this episode is for you. What did you make of Angela's views on governance, ROI, and the next phase of AI adoption, and where do you think businesses are still getting it wrong? Share your thoughts with me.

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