Key takeaway
Eli Lilly's jump to #1 on the CB Insights Pharma AI Readiness Index reflects a broader truth: the pharma companies winning the AI race are those treating AI as core R&D infrastructure, not as an innovation lab experiment.
Lilly jumped to #1, Merck to #2, Roche fell to 5th, while J&J, Novartis, and GSK dropped out of the Top 10. AI in pharma R&D shows huge potential but limited delivery so far.
What the index measures
The CB Insights Pharma AI Readiness Index ranks the top 20 global pharma companies across four dimensions: data infrastructure maturity, AI partnership breadth, internal AI talent density, and demonstrated AI-driven pipeline impact.
The index has become a leading indicator for investors and partners assessing which pharma companies are positioned for the AI-driven R&D paradigm.
Key movers: Lilly rises, Roche falls
Eli Lilly rose to #1 driven by its proprietary real-world evidence platform (100M+ patient records), 14 active AI partnerships (including Recursion, Isomorphic Labs, Insilico Medicine), and 5 of 12 Phase I programs using AI-driven target identification.
Merck climbed to #2 with its Absci partnership for AI-designed antibodies and 400+ ML engineers.
Roche fell from #2 to #5 despite having the industry's richest data assets (Flatiron Health, Foundation Medicine), its AI investments focused more on diagnostics than pipeline acceleration.
Top 10 rankings
The complete Top 10 with scores and key AI initiatives.
| Rank | Company | Score | Change | Key AI Initiative |
|---|---|---|---|---|
| 1 | Eli Lilly | 88 | +2 | 14 AI partnerships; 5/12 Phase I programs AI-driven |
| 2 | Merck | 85 | +2 | 400+ ML engineers; Absci antibody design |
| 3 | AstraZeneca | 83 | , | BenevolentAI partnership; AI clinical trial optimization |
| 4 | Pfizer | 80 | +1 | AI-powered mRNA platform; Albert AI engine |
| 5 | Roche | 78 | -3 | Flatiron/FMI data assets; Genentech AI research |
| 6 | Sanofi | 75 | +2 | Exscientia partnership; AI biologics manufacturing |
| 7 | Takeda | 73 | New | AI drug discovery with Schrödinger |
| 8 | Amgen | 71 | +1 | AI-designed BiTE molecules; deCode Genetics |
| 9 | Boehringer Ingelheim | 69 | New | Google Cloud AI partnership |
| 10 | Bristol Myers Squibb | 67 | +3 | AI biomarker discovery; Recursion partnership |
What separates AI-ready pharma from laggards
Three differentiators emerge. First, data infrastructure is the foundation, every Top 5 company owns proprietary real-world evidence platforms. Second, diversified partnership portfolios outperform concentrated bets. Third, demonstrated pipeline impact separates intention from execution.
J&J, Novartis, and GSK all fell out of the Top 10 due to organizational disruption, corporate restructurings and leadership changes created gaps that competitors exploited.
The laggards are not lacking AI tools; they are lacking the organizational architecture to use them.
About the author
Thomas HagemeijerFounder & CEO of HGM Advisory. Management consultant and HealthTech expert working across the full healthcare ecosystem: pharma, MedTech, investors, startups, hospitals, and policymakers. Investor at Springboard Health Angels. Ambassador at HLTH Europe and HBI. Regular keynote speaker on AI in healthcare and digital health transformation.
