Perspectives on Leading Through Change: Governing with Intelligence
An interview with Justin Forer, Senior Vice President for AI Strategy and Transformation, Comcast
Comcast executive Justin Forer leads AI Strategy and Transformation, working at the intersection of enterprise strategy, emerging technology and operational execution. Prior to joining Comcast, he spent nearly three decades advising major organizations on transformation, governance and technology adoption. He spoke during the Directors Dialogue 2026 session “Perspectives on Leading Through Change: Governing with Intelligence” about what boards and leadership teams should really be paying attention to as AI reshapes organizations.
What does “real AI progress” look like inside a company right now?
Real progress is not about saying you want to “be an AI company.” It’s about understanding how AI helps accelerate the business strategy you already have. The companies making progress have a clear strategy, strong execution, adaptability, and leadership teams that are using AI themselves.
Why do many organizations struggle to move from AI hype to execution?
Because there’s a lot of noise. Everyone is talking about pilots, demos and announcements. But pilots that scale matter. Pilots that don’t are just noise. The real question is: what changed operationally because of AI?
How should boards distinguish between real innovation and “innovation theater”?
Ask what’s measurable. Ask what’s integrated into the business. Ask which pilots scaled and which failed. Twenty pilots waiting for approval is not transformation. Boards should focus on outcomes, not activity.
Ask what’s real, what’s measurable, and what actually changed because of AI.
How should organizations think about AI strategy?
AI should support the existing business priorities. It should be understandable across the company from the C-suite to someone working in a retail store or in a customer-facing role.
Is the pace of AI change different from the pace of previous digital transformations?
Absolutely. We’re not in a world anymore where you can build a three-year roadmap and wait it out. Companies have to operate with much more adaptability.
Something released three days ago might already outperform what you planned three weeks ago.
What makes some organizations faster than others?
Decision-making speed. Data readiness. Risk tolerance. And adaptability. The best organizations can slightly adjust course continuously without abandoning strategy entirely.
How important is AI fluency among senior leaders?
It’s essential. Just like executives have to understand finance and GAAP, they need to understand AI. And not theoretically; they need hands-on experience using it.
How are you building that fluency inside your organization?
We found that taking executives to conferences or showing them flashy demos only works temporarily. What works sustainably is getting leaders to use AI directly in their workflows. Some executives are summarizing emails. Others are experimenting with multi-agent systems. Both are valuable because they’re engaging with AI directly.
What works isn’t wowing executives with cool tech, it’s getting them to actually use AI.
What are the most meaningful metrics to measure AI-enabled innovation?
The metrics that matter are about velocity and acceleration. It’s increased capacity. It’s compressed timelines. It’s doing more projects, faster, with better outcomes.
Can you give an example?
In software development CIOs are always talking about how much of their code is AI-generated. But the bigger opportunity is earlier in the process—business requirements, technical documentation and resource planning. We trained models using historical documentation, and something that used to take weeks now takes minutes. That means more projects are completed faster.
Where should boards get their AI information?
From multiple trusted voices. No one person knows everything right now. I spend a lot of time talking to startups, professors, PhD candidates, CTOs, peers and other AI leaders. Boards need a varied diet of information.
What are the biggest AI risks boards should focus on?
Everyone jumps immediately to today’s risks—bias, hallucinations, compliance. Those matter. But the bigger risks are long-term structural shifts.
What do those long-term risks look like?
First, customer disintermediation. Customers may increasingly go to AI platforms before they come to companies directly. Second, intelligence and labor on demand. AI lowers barriers to expertise and execution. Third, information overload. When high-level analysis becomes inexpensive and instantly available, the challenge becomes deciding what matters.
Should AI be a separate board topic?
Not necessarily. AI doesn’t need to be its own section in board materials or treated as a separate risk category. It can simply be embedded into existing conversations and forums about operations, performance, customer experience and risk.
AI doesn’t need to be a separate board topic; it should just be embedded in everything.
Where should AI sit inside the organization?
We didn’t put AI in tech, finance or HR. We intentionally put AI in strategy.
Strategy becomes the bridge between business priorities and technology implementation.
Are boards using AI to innovate within the boardroom?
Every board member I know is experimenting with AI in some form, usually summarizing reports or preparing questions. The real value of AI will be helping directors explore issues faster and ask better questions.
How would you describe this moment in AI transformation?
This is bigger than any other technology cycle. AI is fundamentally reshaping how organizations operate, communicate, compete and govern.
The challenge isn’t just building AI capability, it’s making that capability understandable, actionable, and aligned across leadership and the board.
Can AI replace human judgment in governance?
Not today. AI can support inquiry, analysis and preparation. But in today’s world, accountability, fiduciary responsibility, and judgment remain human responsibilities.
