AI in life sciences: 6 takeaways for strategy, risk and real-world use

Life sciences leaders face a major gap in AI strategy linking governance, data management, and business value, with initial AI use dominated by productivity gains rather than sector-specific impact. Data quality, risk management, and governance are critical challenges slowing meaningful AI adoption, while many prefer buying AI tools over building them internally.

This Wire brief sits within Fusion42's coverage of AI Frontier Models, Biotech and Digital Health.