Inside Google Deepmind's CEO's Plans For The Future of AI
As AI reshapes industries from healthcare to search, few people are as central to that transformation as Demis Hassabis, Co-Founder and CEO of Google DeepMind.
Speaking with Fortune, Demis laid out a strategy that spans AI, breakthrough drug discovery and the deployment of AI across billions of users.
It is a vision rooted in scientific ambition, operational rigour and a commitment to responsible innovation.
Demis traces his ambitions back to childhood fascinations with chess and cosmology. "I've always been interested in the big questions. What's actually happening here in the universe? The nature of consciousness, all of these types of things," he said.
Chess, he explains, sharpened his thinking about thinking itself. "And then that got me thinking about thinking - and how does the brain work?"
When he co-founded DeepMind in 2010, he said the mission was explicit: "We set out with the mission of solving intelligence and then using it to solve everything else." The goal was AI, first applied to scientific discovery.
That mission drove the 2014 sale to Google, he explained: "What mattered to me was not the money, it was the mission, and being able to accelerate out progress towards artificial general intelligence.
"They [Google] had obviously enormous computing power, and we see today how important that is for developing intelligence."
AlphaFold and the drug discovery engine
Within Alphabet, Demis pursued high-risk, long-horizon science projects. AlphaFold became the clearest proof point. "It's basically a solution to a 50-year-old grand challenge in biology - can you determine the 3D structure of a protein just from its amino acid sequence?" he explained.
The system folded "all 200 million proteins known to science" and made the results freely available. "So now over 3 million researchers around the world make use of AlphaFold every day," Demis said.
But proteins are only the beginning. Drug development typically takes "like on average, 10 years" with "only like a 10% success rate". Through Isomorphic Labs, Demis is building "a general drug discovery engine platform" that inverts this process.
"You basically do your search and your hypothesis searching in silico, and that's hundreds, thousands of times more efficient than doing it in a wet lab," he said.
The company now has 17 active programmes, he added, and early-stage cancer therapies in pre-clinical trials.
Rebuilding Google's AI engine
In 2023, Google unified DeepMind and Google Brain under Demis to consolidate talent and commute. "We needed to combine all of our easels together," he said.
His approach emphasises research first, product velocity second. "None of it matters if your models aren't best in class," he said, adding that Gemini became the centrepiece, alongside image and video models, with infrastructure rebuilt to feed improvements directly into Search, YouTube, Chrome and the Gemini app.
Demis said: "In today's very noise world, it's important to consistently deliver good, rational decisions with minimal drama", emphasising his focus on intensity and efficiency.
Google DeepMind, he explained, functions as "the engine room of Google", powering the company's broader AI capabilities.
Speed, efficiency and a universal assistant
Demis stresses that AI is dual-use. "Harmful actors, bad actors could use it for harmful ends," he said. Commercial success, he argues, underpins public benefit. "We have to make sure that the engine and the economic engines work as well, so we have enough money to fund our research and fund things like AlphaFold and give it to the world for free."
Looking ahead, he envisions autonomous agents and devices that deliver a seamless AI experience. Demis describes a "universal assistant" that works across devices, from phone to browser to smart glasses, integrating context to assist in everyday life.
His long-term vision spans science and society. "Done right, in 10-15 years time, we'll be in a new golden era of discovery," Demis said. "I think human health will be revolutionised."



