According to Forbes, the ninth annual Imagination in Action forum took place on January 21, 2026, in Davos, convening 275 speakers for a day of intensive AI discussions. The event, curated as a counterpoint to hype-driven tech showcases, featured a massive roster including former Google CEO Eric Schmidt, Meta’s former Chief AI Scientist Yann LeCun, MIT President Sally Kornbluth, and musician will.i.am. A major focus was the move beyond today’s large language models toward “physical AI” systems integrating physics and sensory data. The forum was convened in collaboration with MIT, Stanford, Deloitte, and Forbes, with a central conclusion emerging: AI strategy is shifting decisively from experimentation to institutional transformation.
The Hype Is Over
Here’s the thing about Davos. It’s easy to be cynical. But this report makes a compelling case that the conversation there has fundamentally matured. The event was explicitly framed as a “counterpoint to hype-driven technology showcases.” That’s a big deal. It signals that the era of just being wowed by a chatbot’s poetry is over. Now, the real work begins. And the real work, as the speaker lineup shows, is messy, multidisciplinary, and deeply institutional.
Who’s In The Room Matters
The diversity of the 275-person speaker list is the story. This wasn’t just a Silicon Valley love-in. You had foundational researchers like Yann LeCun and Yoshua Bengio debating the future of model architectures. But right alongside them were CEOs from Deloitte and Bain Capital talking about scaling and markets. You had MIT’s president and lab directors wrestling with talent pipelines and education. And crucially, you had policymakers from India, Israel, the UAE, and the UN. That mix forces a different conversation. It’s no longer “what cool thing can we build?” It’s “how do our businesses, governments, and universities survive and adapt to what’s being built?” That’s a harder, more important question.
The Next Big Bet: Physical AI
The most interesting technical takeaway is the pivot to what they’re calling “physical AI.” LeCun’s argument that the next breakthroughs depend on “world models” integrating hard sciences like physics and chemistry is a direct challenge to the current text-and-image paradigm. Think about what that means. We’re talking about AI that understands the real, physical world well enough to transform manufacturing, energy logistics, and scientific discovery. That’s the realm of heavy industry, complex supply chains, and hard engineering. It’s a different ballgame requiring different infrastructure, different data, and different safety protocols. It’s also where the most profound economic impact will likely be. If you’re in industrial tech, this is the horizon you need to be watching.
Institutional Transformation Is The Only Game
So what’s the bottom line from under the Davos Dome? The summit’s central conclusion feels spot-on: the phase of AI as a cool departmental pilot project is dead. The focus is now on “institutional transformation.” Speed of decision-making, workforce adaptation, and strategic positioning matter more than which LLM vendor you pick. This is where the rubber meets the road. It’s about retraining thousands of employees, overhauling century-old business processes, and making billion-dollar bets on new infrastructure. The money movers and policy leaders in the room underscore that this is now a capital allocation and governance challenge as much as a technical one. The conversation has finally caught up to the reality. The easy part—being amazed—is over. Now comes the hard part: changing everything.
