スナップチャート
A recent Bain survey reveals a top reason some life sciences companies feel stuck in the early days of AI adoption: insufficient C-suite sponsorship. Passive support isn’t enough for progress. To capture real value, executives at early AI explorers can regularly review AI initiatives using measurable KPIs and hold initiative leaders accountable while also clearing roadblocks. Of course, that’s easier said than done. But executives can make it more manageable by concentrating their time on a small handful of high-value use cases, establishing clear guardrails, and moving quickly to organization-wide scale.
In pharma and medtech, IT and tech functions have historically played a supportive back-office role. Now, AI’s strategic importance and potential to completely change workflows require rethinking traditional operating models. This comes with large price tags and unfamiliar risk profiles, meaning AI demands a front-and-center seat with the C-suite. The best companies will explicitly link AI to enterprise strategy, executive accountability, disciplined capital allocation, and centralized governance.
From Silos to Pods: Scaling AI in Life Sciences
Cross-functional collaboration is the real differentiator between those that see meaningful returns and those that don’t.
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First published in 1月 2026