Rene Haas is betting on machines.
The CEO of Arm Holdings says AI will help find a cure for cancer “within our lifetimes,” even though the technology still faces stubborn limits in biology, computing power, and the physical supply of chips. In a BBC interview with Faisal Islam, Haas said, “I believe in our lifetime, AI will help cure cancer.”
Haas’s claim rests on a problem that humans cannot yet model properly. “Modelling how a DNA marker is impacted by cancer – it’s too complex a problem, not only for humans today, but the computers that run AI,” he said. As models receive more data and computers become more sophisticated, Haas expects them to solve problems that remain beyond human research today.
AI Could Compress the Drug Pipeline
Drug development can take 20 years, and around 95% of research and development efforts to develop drugs fail. Haas said AI will shorten the time needed to invent and test new drugs, with AI modelling supplementing or replacing some human trials.
That does not make the science simple. It does mean researchers could use computer models to test more possibilities before moving into physical trials, cutting time from a process famous for consuming both money and patience. Pharmaceutical development has never lacked paperwork; it has lacked reliable shortcuts.
Haas has direct links to that industry. He stepped down from the board of British pharmaceutical giant AstraZeneca in April 2026, after becoming Arm’s CEO in February 2022. He joined Arm in 2013 and also serves as chief executive of SoftBank’s international business, while SoftBank holds a stake in OpenAI, the maker of ChatGPT.
AI-powered medical tools already show a narrower version of this promise. Funding for AI-powered X-ray tools helped more than 4 million patients receive faster lung diagnoses, offering evidence that AI can affect care before it solves the deeper biological questions surrounding cancer.
The Hardware Bill Is Becoming the Real Bottleneck
The path from prediction to treatment depends on infrastructure that does not arrive by wishful thinking. The industry cannot manufacture enough chips to meet demand, creating a supply-constrained environment as large AI models consume vast amounts of memory and computing power.
Technology companies are committing hundreds of billions of dollars to new data centers, but the buildings still need processors. New semiconductor fabrication plants can cost tens of billions of dollars and take two to three years to build, creating a physical constraint on expanding AI infrastructure.
“We need more fabs before we can put a data centre in space,” Haas said, referring to a concept also mentioned alongside Elon Musk and Jeff Bezos. Even the escape plan for data centers begins with factories on Earth. Space, for once, is not the hard part.
Arm’s business offers a measure of how quickly demand is moving. Demand for its Neoverse product rose from around $1 billion to more than $2 billion within five months, with Meta, Oracle, Cloudflare, and SK Telecom among its customers.
More than 350 billion chips using Arm technology have shipped worldwide, and Arm’s designs sit inside almost every smartphone on Earth. Apple, Samsung, Qualcomm, and Nvidia use those designs, while Arm employs more than 7,000 staff, including about 3,000 in the UK.
Arm is valued at $269bn (£199bn), giving Haas a platform for a prediction that reaches well beyond chip architecture. His argument is not that AI has already cured cancer, or that current systems can model every DNA interaction. It is that better models, more computing power, and enough chips will eventually change what researchers can test.
That final requirement is less glamorous than a medical breakthrough, but no less important. AI may shorten drug discovery and help decode cancer biology; first, the industry has to build the machines capable of doing the work.
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