Pharma leading payers, providers in AI adoption

Despite the growing hype around AI in healthcare, a new industry survey suggests a widening adoption gap between sectors.

According to Define Ventures' latest AI report, only 53% of payer and provider executives identify AI as an immediate strategic priority – compared with 65% of their pharmaceutical peers.

The report was based on interviews with more than 40 executives across 15 of the top 20 global pharmaceutical companies.

Pharmaceutical companies appear to be pulling ahead, not only in strategic prioritization of AI, but also in building governance structures.

While 83% of pharma executives say their organizations have formal governance committees in place for AI oversight, just 73% of payer and provider respondents say the same.

The divergence is most pronounced in how the sectors apply AI today. Providers and payers are largely focusing on near-term, operational use cases that present low risk.

“AI is helping pharma companies unlock new levels of efficiency, rethinking workflows to optimize both speed and quality without compromising scientific integrity,” Lynne Chou O'Keefe, founder and managing partner of Define Ventures, told Healthcare Finance News.

For example, 83% of provider organizations report deploying or piloting ambient clinical documentation tools to reduce the administrative burden on physicians.

O'Keefe explained that moving from pilots to scaled implementation often requires significant internal efforts, especially as organizations mature from fragmented, department-led efforts toward more centralized, enterprise-wide strategies.

“We’re seeing this shift supported by formal governance structures,” she said. “Implementation itself is also one of the biggest hurdles.”

Leaders are addressing this challenge by creating sandbox environments to test solutions while preserving data integrity and compliance, enabling safe experimentation and evaluation of new models without disrupting core systems, she explained. 

The study also found 68% of payer respondents are using AI to optimize call center performance – a straightforward way to reduce cost and improve member experience.

In contrast, pharma leaders are prioritizing AI tools that can drive scientific discovery, drug development and patient engagement at scale.

Their stronger in-house data infrastructure may be a factor. When asked about data strategy, 59% of pharmaceutical executives say they are relying primarily on internal builds to support AI systems, compared with only 28% of payer and provider respondents.

“We believe external solutions must be transparent, differentiated, and capable of delivering ROI without relying on immediate access to internal data,” O'Keefe said. “Just as critically, they must earn the trust of internal teams from day one and integrate with minimal friction.”

In leading organizations, C-suite-level AI champions are emerging to bridge technical, scientific and commercial teams – aligning incentives and creating the scaffolding for scaled, enterprise-wide AI adoption, she added.

“There’s a clear appetite for automation in areas with minimal regulatory or reputational risk – what many describe as ‘low-hanging fruit’ – but we also see pharma ideally positioned to get high ROI in use cases across the value chain,” O'Keefe said.