Peter Lee, who has publicly confirmed his departure from the presidency of Microsoft Science, is set to take on a newly established artificial intelligence advisory position within the Mercedes Formula 1 team. Over 16 years at Microsoft, Lee directed the company's science and research portfolio, focusing on ways artificial intelligence could support doctors and researchers tackling complex questions in the physical, biological, and medical sciences.
Four areas will define his work at Mercedes: applying artificial intelligence to the team's engineering and physics challenges, dismantling the information barriers that separate departments, constructing financial and forward-looking data models, and offering guidance on how governing bodies in the sport are likely to approach AI regulation. The role he will carry remains under negotiation, though a one-year deal with a second-year option is the arrangement being put forward. In his own words, racing has long been an ambition he has held.
Speaking with reporters, Lee traced his path from childhood kart racing and noted that an invitation from the Mercedes team had come as something of a surprise — one he received with gratitude. A team spokesperson had not responded to a request for comment ahead of the story's publication.
Lee's move points to a broader pattern in which artificial intelligence tools are altering workforce structures across corporate hierarchies, including at the executive tier. Growth in artificial intelligence has driven intensified competition for skilled workers, with employers well beyond the technology hubs of California working to attract and retain that expertise. In a separate development, Dr. James Smith, who brought with him a background that included a stint at DeepMind, the artificial intelligence laboratory operated by Google, was appointed to the role of chief information officer at Williams Formula 1, with the move taking effect in June.
The shift in Lee's role is unfolding against a backdrop of broader personnel turnover at Microsoft, where CEO Satya Nadella has been steering the organisation toward capturing enterprise and cloud opportunities within the AI sector. Two departures from Microsoft's leadership ranks were disclosed around the same time: Ryan Roslansky, who held the LinkedIn chief executive post alongside an executive vice president role, and Frank X. Shaw, the company's chief communications officer, both indicated they would be stepping down. Phil Spencer, who oversaw the gaming division, and Rajesh Jha, who held the executive vice president post spanning experiences and devices, also stepped away from their roles at the company during the first part of this year.
Microsoft described Lee's role there as driving faster progress across the physical, biological, and medical sciences by putting artificial intelligence and other emerging technologies to work in those fields. Diagnostic systems, precision medicine platforms, and tools built for clinicians all fell within the scope of his professional contributions. Among those contributions was InnerEye, a tool designed to handle the labour-intensive process of outlining tumours and the healthy tissue around them ahead of radiation therapy planning, relying on automation to carry out that work.
Prior to GPT-4 reaching the public, Lee contributed to evaluating the model's capabilities and exploring where it might prove useful within medical practice. In 2024, Time magazine named him among the hundred people judged most influential across health and life sciences. A tool unveiled by Microsoft in 2025, built on artificial intelligence, was reported by the company to outperform a panel of physicians on disease detection by a factor of four, while operating at considerably lower expense.
Arrangements with Mayo Clinic and Harvard Medical School fed into product development — including work on the Copilot AI assistant — though that tool has since been steered toward enterprise applications rather than general-public or healthcare-oriented ones. Drawing a comparison between Formula 1 racing and medicine, Lee noted that the two fields diverge in many ways yet converge around a common pressure point: teams of extensively trained people face consequential decisions rapidly, often without complete information, whether in patient care, medical investigation, or on the race circuit. He described how AI tools can be woven into this process in ways that genuinely support rather than pull attention away from the work at hand as an open and worthwhile question.
