What You Should Know:
– Define Ventures, one of the largest venture capital firms focused on early-stage health tech companies, today released a report revealing how Big Pharma is accelerating investment in AI to counter rising cost pressure, regulatory shifts, and growing competitive urgency.
– The report is based on in-depth surveys and interviews with over 40 executives, including leaders from 16 of the top 20 pharma companies and major players like Amazon Web Services, NVIDIA, Oracle Life Sciences, Tempus AI, and Datavant, the report uncovers a decisive shift towards enterprise-scale AI deployment.
From Pilots to Enterprise-Scale: Pharma’s AI Strategy Matures & Accelerates
Bringing a new therapeutic to market is a lengthy and expensive process, with timelines and costs more than doubling over the past two decades (10–15 years and $2.6 billion, respectively). Against this backdrop, combined with cost-cutting and pricing pressure from the Inflation Reduction Act, pharma C-suite leaders increasingly view AI as a strategic necessity.
This urgency is translating into meaningful action and investment:
- Immediate Priority: 70% of pharma leaders now consider AI an immediate priority, a number that rises to 85% among the top 20 pharma companies.
- Increased Investment: Despite overall budget contractions, 85% of executives are increasing their AI investments (40% significantly, 45% somewhat), directing spend toward improving productivity, accelerating drug development, and protecting margins.
- Key Priorities: 100% of respondents cite reducing administrative burden and improving workforce efficiency as AI success metrics, with R&D efficiency (80%) and revenue acceleration (75%) closely following. AI is seen as both an efficiency tool and an engine for scientific innovation.
The Build-vs-Buy Mentality Is Breaking Open
Historically, pharma companies favored building AI solutions in-house, especially for data and application layers, viewing proprietary data and scientific workflows as core strategic assets. However, this mindset is shifting. While 30% of pharma leaders still plan to primarily build in-house, 40% expect to split efforts between internal development and external partnerships, and 30% are prioritizing external-first strategies.
Despite growing openness, satisfaction with external vendors has been mixed: only 35% reported a somewhat positive experience, 40% neutral, and 5% somewhat negative, indicating high expectations for performance, seamless integration, and early ROI.
Big Tech Becomes Embedded in Pharma’s AI Stack
The report highlights the growing role of Big Tech and consulting firms as deeply embedded strategic partners in pharma’s AI transformation. Cloud providers, in particular, are moving up the stack, offering life science-specific solutions, including infrastructure, domain-tuned models, and co-development opportunities.
Current AI Investment Focus: Low-Risk, High-Impact Efficiency Gains
Pharma companies are prioritizing AI investments in areas with low risk and immediate returns, with a clear emphasis on improving operational efficiency.
- Medical Writing: 94% of respondents identified medical writing as a top AI priority for the next year, reflecting strong appetite for automation in high-volume areas with minimal regulatory or reputational risk.
- Therapeutic Discovery: 80% of leaders are focused on reducing the cost of therapeutic discovery, streamlining tasks like literature reviews, hypothesis generation, and lab automation, and building infrastructure for complex multimodal data.
Pharma Outpacing Healthcare Peers in Operational Readiness
Pharma organizations are notably ahead of payers and providers in operational readiness for AI:
- Governance: 80% of pharma companies have formal AI governance committees, compared to 73% of payers and providers, indicating strong institutional alignment across data, technology, and business leadership.
- Funding Models: Pharma’s funding models demonstrate a shift from fragmented, department-led efforts to more centralized, enterprise-wide strategies. Only 20% of AI budget is allocated by innovation teams in pharma companies, compared to 60% for payers and providers, reflecting pharma’s readiness to scale AI.
“Pharma’s AI future will be defined in the next 12 to 24 months,” said Lynne Chou O’Keefe, Define Ventures founder and managing partner. “What we’re seeing is a decisive acceleration to enterprise execution — with leaders embedding AI into core workflows to drive speed, efficiency, and real ROI. But internal teams can’t do it alone. This moment is a generational opportunity for startups that are ready to scale, integrate seamlessly, and speak pharma’s language.”
