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Only 10% of pharma companies using AI are truly extracting value from it, according to a recent survey by Bain & Company, conducted in partnership with Bessemer Venture Partners and Amazon Web Services.
What sets these leaders apart? They’ve established the right foundation, starting with a clear commercial AI strategy and use case roadmap. They never deploy an AI solution without complementary process redesign. That includes evolving how teams work and putting real energy into behavior change. They also have effective, forward-looking AI governance and risk management.
Most pharma companies, however, are still in the early days. About half have yet to pilot AI solutions. The good news? It’s not too late to catch up.
The fastest path forward starts with bold ambition. Leaders will aspire to set the industry standard for AI-enabled teams and personalized healthcare professional (HCP) engagement. That means using AI to power dynamic content engines for HCPs and equip field teams with next-best actions and training.
But ambition alone isn’t enough. Real ROI requires the right capabilities. Maximizing value creation goes beyond having the right data, tech, talent, roles, processes, and governance. Successful organizations will rally around fail-fast experimentation and a test-and-learn culture. Meanwhile, companies that only deploy AI solutions once they have validated pilot results will quickly fall behind.
Based on our discussions with large pharma companies, we’ve found that most have invested heavily in data and tech infrastructure. However, very few have started investing in their capacity for change. This will be the greatest hurdle—and the greatest differentiator. The leaders of tomorrow will be those that put their dollars and focus behind rethinking their ways of working.
Generative AI Is Gaining Ground with Commercial Pharma Teams
Companies have long focused on R&D, but leaders are growing confident in commercial use cases.
The Healthcare AI Adoption Index
A survey of more than 400 healthcare buyers reveals what’s fueling their AI experimentation and pinpoints opportunities for innovation partners.
Published in July 2025
