Baillie Gifford Investment Expert: Excess Returns in Healthcare AI Depend on a Few Companies Solving Hard Problems, Not Market Size
Hamish Maxwell, an investment specialist at the Scottish Mortgage Investment Trust, outlines the thesis for healthcare AI investment: the appeal lies not in market size, but in a few companies using AI, data, and biotechnology to solve hard problems like cancer, diabetes, and brain diseases in novel ways; he also frankly notes that AI advancements do not automatically translate into medical breakthroughs, with slow clinical data generation and long regulatory approval cycles being core bottlenecks.
The investment logic of the Scottish Mortgage Investment Trust is not built on the common-sense notion that 'the healthcare market is large.' In arguments published in November 2026, Baillie Gifford investment specialist Hamish Maxwell explicitly stated that what truly attracts them is a few companies attempting to solve extremely difficult problems with new methods, thereby potentially gaining disproportionate returns. He wrote, 'The attraction is not just that healthcare is a large market, but that we see a few companies trying to solve very hard problems in novel ways, with potentially outsized rewards.' This judgment forms the core premise of the entire argument: the investment value of healthcare AI comes from the intersection of problem difficulty and method novelty, rather than track capacity.
When explaining how value is specifically created, Maxwell provided two types of mechanisms. The first is the data moat. Taking Tempus AI as an example, the company organizes and analyzes clinical and molecular data to help doctors make better decisions and researchers develop better therapies. Maxwell emphasized that in healthcare, data only constitutes a true competitive barrier when it is 'unique and difficult for competitors to replicate or buy.' Tempus claims connections with more than half of US oncologists and over 65% of US academic medical centers; Maxwell's reasoning is that the more decisions its data influences, the more valuable and harder to replace it becomes. This logic defines data advantage as an asset that deepens with use rather than decays over time.
The second mechanism is platform economics. Taking Moderna as an example, its most well-known product is the COVID-19 vaccine, but its broader ambition is to use messenger RNA (mRNA) as a programmable drug. In 2026, its personalized melanoma therapy (developed in collaboration with Merck and used in combination with Keytruda) became the first mRNA-based cancer therapy to succeed in Phase 3 clinical trials. Maxwell's reasoning is that drug development is typically slow, expensive, and highly specific, but a platform that can generate multiple products from the same technological foundation offers 'repeated innovation,' potentially changing the structure of economics and the scope of what can be created. Insulet’s Omnipod insulin delivery system demonstrates another dimension: for patients with chronic conditions, better devices can change lives, generating recurring revenue, patient loyalty, and long-term growth.
However, Maxwell inserted a key and frank limitation in his argument: one should not assume medicine will keep pace simply because AI is advancing rapidly. He wrote that AI technology relies on vast, diverse datasets and rapid feedback; in contrast, the clinical data relied upon by drug trials is slow and expensive to generate, designed to satisfy regulators rather than train algorithms. It may take years for medical regulators and clinical practice to catch up with genuine breakthroughs. This bottleneck means the path from innovation to impact may be 'slow and painful,' and 'few companies get to reshape the future of human health.' This is not an abstract warning, but a structural constraint directly affecting the time scale of investment returns.
Maxwell ultimately framed this argument as a belief in 'continuous reinvention' rather than a bet on a single technology, disease area, or regulatory outcome. Holdings in the healthcare innovation theme account for approximately 7% of the Scottish Mortgage portfolio. He acknowledged that 'some innovators will fail, others will disappoint,' but believed the returns are unusually alluring—supporting those companies that might create significant economic value and contribute to a world of longer, healthier lives. This conclusion preserves the conditional nature of the argument: it is not a prediction of success, but an argument that under specific mechanisms (deepening data moats, platform repeated innovation, eventual completion of clinical translation), the success of a few companies can generate returns far exceeding their current scale.
Notably, this argument comes from Baillie Gifford, which manages the Scottish Mortgage Investment Trust, a fund known for holding high-growth companies for the long term, having held genomic sequencing pioneer Illumina for a long period (2011 to 2023) and supporting it through a hostile takeover bid. Maxwell used this experience as context for understanding 'what better biological insight can deliver.' The article did not disclose specific holding costs, current valuation multiples, or expected return figures; its value lies in mechanism explanation and honest acknowledgment of bottlenecks, rather than verifiable performance records.