Our Take
Biotech is fixating on geopolitics and AI cost instead of the real problem: proving AI actually works in drug discovery at scale that matters.
Why it matters
The sector faces three simultaneous pressures—Chinese competition, unpredictable federal policy, and AI's unproven ROI—forcing executives to pick which threat to address first. None of them have clear answers.
Do this week
Biotech R&D leads: document your current AI spend per discovery program and benchmark it against one competitor's public disclosures this quarter so you know if you're burning cash on hype.
What the industry is worried about
The BIO 2026 conference in San Diego, the industry's flagship annual gathering, surfaced three overlapping concerns among biotech and startup executives. China's expanding role in drug development emerged as a central topic, with attendees focused on how to compete in a landscape where foreign competitors are accelerating their own capabilities. Simultaneously, executives discussed how to navigate Trump administration governance and pricing policies that could affect profitability. The third thread running through conversations was artificial intelligence and its costs. Early AI deployments in biotech are yielding clues about competitive advantage, but the economics remain unclear.
The conference floor reflected this tension. Executives moved between pavilions representing different countries and states, pausing at a South Korean contract manufacturer's booth. The energy was divided between watching the World Cup on a giant screen and thinking about how to beat back pricing pressure while moving quickly on AI.
The missing metric: does AI actually reduce drug development cost?
Biotech is chasing three separate problems at once, but the conversation lacks hard numbers on what matters most. Executives are positioned as if they must choose between matching China's scale, preparing for policy shifts, and deploying AI. But none of these choices matter if the underlying question goes unanswered: can AI reduce the time or cost of bringing a drug to market by a measurable amount?
The industry is treating AI as a competitive necessity without clear evidence that it is. Early results show "clues about how to use the technology to gain a competitive edge," per reporting from the conference, but clues are not proof. If biotech CEOs spent as much time benchmarking their AI spend against documented deployment wins as they spend on China strategy, they might discover they are paying for optionality rather than advantage.
What R&D teams should track now
Biotech research leads need to separate signal from noise in their own organizations. Document what you are spending on AI per discovery program. Compare that spend against the time saved, molecules advanced, or clinical trials started. Then compare your program's ROI against one peer's public disclosures or earnings calls where they mention AI deployment. You will quickly see whether your AI spend is moving the needle or anchoring your margin.
The geopolitical and regulatory conversations at BIO are real and necessary, but they are also cover for the fact that most biotech companies do not yet know whether AI makes them faster or just more expensive.