4 min read
Microsoft Chairman and Chief Executive Officer Satya Nadella delivered a keynote at the World Economic Forum 2026 in Davos, Switzerland, where he underscored the importance of moving artificial intelligence beyond hype. He emphasized that there is a need to approach AI on a more practical, measurable basis across global industries.
“So many people talk about there may be an AI bubble,” he told Larry Fink, Chairman and CEO at BlackRock. “The most important thing that we see as an investor is the democratization of technology and the diffusion of that technology really does then transform the demand, and the companies or the countries that diffuse it fastest are going to be the ultimate winners – not the technology creator.”
Speaking alongside global executives and policymakers, Nadella argued that AI’s long-term success depends on delivering real outcomes across the wider economy, from healthcare and education to public services and agriculture, and not just buoying tech-sector valuations.
“We as a global community have to get to a point where we are using [AI] to do something useful that changes the outcomes of people and communities and countries and industries,” he said.
Nadella’s emphasis on practical impact echoes current research published by the World Economic Forum’s MINDS initiative, which highlights companies around the world using AI to improve sustainable energy, healthcare delivery, and climate resilience, offering evidence that measurable real-world applications are possible when technology is aligned with societal needs.
At Davos, the Microsoft CEO repeatedly warned that AI risks becoming a bubble if its benefits remain confined to a handful of tech firms or wealthy economies, noting that equitable distribution of AI’s advantages is essential for broad adoption and long-term growth. “If AI only benefits tech firms, it’s a bubble,” he said, underscoring that diffusion of AI across sectors and geographies must be a strategic priority.
Larry raised the issue of how AI can be expanded beyond technologically mature regions, pointing out that most real-world deployments remain “heavily weighted towards those who are educated or educated economies,” leaving large segments of the global population outside the reach of AI-driven progress. The central problem, as he framed it, is how to connect communities that have yet to meaningfully benefit from these technologies.
Satya responded by arguing that the divide is less about availability and more about relevance, emphasizing that “these models and their output are pretty much available everywhere.” In his view, the missing link lies in practical, locally meaningful applications that people can actually relate to and use.
To illustrate the point, he drew a parallel with the early adoption curve of smartphones, noting that it “took a long time” for the technology to penetrate all regions, but that disparity has steadily diminished over time as use cases became clearer and infrastructure improved.
He then cited a concrete example from the early days of generative AI, recalling:
“One of the demos I always go back to – I think this was even in the beginning of 2023 – was a rural Indian farmer who was able to use a bot built on, I think a very early GPT, essentially to reason over some farm subsidies that he heard about… I do think it’s in our hands even in the global south to use it to create, I would say, more of an opportunity when there isn’t one.”
Nadella also highlighted that access to capital, infrastructure, and skills will determine which countries and industries succeed in harnessing AI’s potential, particularly in the Global South. He stressed that investment and policy alignment are necessary to ensure AI drives productivity and economic opportunity beyond affluent markets.
Industry leaders at the forum similarly emphasized the need for responsible, human-centered AI, with panels noting that technology must balance innovation with ethical considerations and workforce impacts.
Business executives pointed out that while AI can revolutionize fields like healthcare and energy, it also poses risks such as job disruption, data inequality, and environmental costs, which policymakers must address collaboratively.
You can watch all of his talk here:
