Could artificial intelligence really be the cure-all we’ve been waiting for? According to Demis Hassabis, the man leading Google DeepMind, we might be just 10 years away from solving every disease known to humanity. And the wild part? Even his biggest rivals seem to agree.
The comment didn’t come in some random TED Talk or speculative panel. It dropped during a prime-time 60 Minutes interview on Sunday — and it’s stirring up serious buzz across the tech and health worlds. Hassabis says drug discovery, clinical trials, treatments — all of it — could be radically compressed by AI, turning the current slog of a decade-long, billion-dollar process into something closer to a sprint. Weeks, even.
The billion-dollar headache AI wants to fix
Hassabis didn’t mince words. Drug development, he said, is “a ten-year, multi-billion-dollar process” right now. And that’s for just one successful drug. Many more fail before ever reaching the market.
“We can maybe reduce that down from years to maybe months or maybe even weeks,” Hassabis said on 60 Minutes. “Which sounds incredible today, but that’s also what people used to think about protein structures.”
That last bit is a nod to AlphaFold — the AI system from DeepMind that cracked the structure of over 200 million proteins. A breakthrough many thought was decades away. And it happened in 2020.
Here’s what traditional drug discovery looks like:
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Time: Around 10–12 years
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Cost: Roughly $2.6 billion on average (according to Tufts Center for the Study of Drug Development)
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Success Rate: Less than 12% of drugs entering clinical trials actually make it to market
With AI stepping in, all three of those metrics could change — drastically.
Aravind Srinivas jumps in with rare praise
The unexpected twist came from Aravind Srinivas, the CEO of Perplexity AI. Usually, you’d expect some healthy competition between companies working on rival tech. Not this time.
Reacting to the clip of Hassabis’ interview, Srinivas wrote on X (formerly Twitter): “Demis is a genius and he should be given all resources in the world to make this happen.”
That’s not the kind of thing CEOs usually say about their competition.
Especially not when Perplexity’s core product — an AI-powered search engine — is trying to chip away at Google’s dominance.
Still, Srinivas didn’t hesitate. And that says something.
Curing all diseases? Is that even possible?
Skepticism is fair. “All diseases” is a huge claim. But Hassabis genuinely thinks it’s within reach.
“I think that’s within reach. Maybe within the next decade or so, I don’t see why not,” he told CBS. He pointed to AI’s ability to understand biological complexity faster than any human ever could.
It’s not about replacing doctors. It’s about giving them better tools.
Take this example: In 2021, DeepMind’s AlphaFold was used to help figure out the structure of SARS-CoV-2 proteins — something that helped accelerate COVID-19 research. That was just the start.
Now, the company wants to apply similar AI models to:
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Rare genetic disorders
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Cancer drug matching
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Personalized treatment plans
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Even aging-related diseases
Between ambition and reality lies regulation
Of course, tech optimism often crashes into the wall of real-world regulation. You can’t just release an AI-generated drug without trials. And AI models aren’t immune to bias or error.
Here’s a quick comparison of how AI changes the drug development pipeline:
| Phase | Traditional Method | AI-Augmented Method |
|---|---|---|
| Target Identification | Years of lab research | Weeks via AI protein mapping |
| Drug Design | Slow chemical synthesis | Instant molecular generation |
| Pre-Clinical Testing | Manual testing on cell lines/animals | Simulated models to narrow options |
| Clinical Trials | Sequential phases over years | Parallel simulations + trial prediction |
Even with AI cutting corners on research, human trials still take time. That means full cures in 5–10 years is an optimistic best-case — not a sure bet.
The hype vs hope debate gets louder
Every time a tech exec makes a bold health claim, critics come out in full force. Remember Theranos? Elizabeth Holmes? Over-promising can wreck trust.
Hassabis isn’t hyping a product he’s trying to sell. And Srinivas backing him up only adds to the legitimacy. It’s more like scientists seeing a glimpse of something big — and agreeing that it deserves attention.
Even so, experts warn against treating AI as a silver bullet. Disease is complex. Social, genetic, economic. Some things, like health inequality, AI won’t fix alone.
Still, it’s hard to ignore the energy in the room right now.
“Appealing to human biology using tools we never had before — that’s where AI shines,” Hassabis said.
