Pharma Boosts AI Spending Amid Cost, Efficiency Demands

Pharmaceutical companies are accelerating investments in AI in response to rising cost pressures, increasing regulatory demands, and intensifying market competition, reports venture capital firm Define Ventures.

“Amid the promise of transformative change, pharmaceutical firms must grapple with a myriad of challenges in implementing AI initiatives while navigating unprecedented opportunities for growth and innovation,” writes Sandra Sánchez, President and CEO, PharmAdvice, on MBN.

The report is based on input from over 40 executives, including leaders from 16 of the top 20 global pharmaceutical companies and key players such as Amazon Web Services, NVIDIA, Oracle Life Sciences, Tempus AI, and Datavant. It presents a clear shift from experimentation to enterprise-scale AI deployment.

According to Lynne Chou O’Keefe, Founder and Managing Partner, Define Ventures, the next 12 to 24 months will be pivotal in shaping pharma’s AI trajectory. “What we are seeing is a decisive acceleration to enterprise execution,” says O’Keefe.

AI has the potential to revolutionize the pharmaceutical industry by accelerating drug discovery, improving patient outcomes, and reducing healthcare costs. The pharmaceutical sector, facing long development cycles and high costs is turning to AI as a strategic lever to enhance speed and productivity.  Around 70% of pharma leaders now consider AI an immediate priority, and 85% of executives report increasing their AI investments.

While pharma has traditionally favored building AI tools internally, the landscape is shifting. Only 30% of executives surveyed said they will continue to prioritize in-house development. A further 40% plan a hybrid model, combining internal resources with external vendors, and another 30% are moving toward externally driven strategies.

Despite this openness, many pharma leaders express dissatisfaction with current vendor partnerships. Just 35% rated their experiences positively, indicating a gap between expectations and outcomes. This underscores the need for external solutions that are tailored to pharma’s complex regulatory environment and capable of demonstrating early return on investment.

Cloud providers, traditionally seen as infrastructure partners, are now developing life sciences-specific tools and services, further integrating into pharma’s AI value chain. This deeper involvement is reshaping the market dynamics for AI startups, which must now differentiate themselves not only through innovation but also through seamless integration and domain relevance.

Compared to their peers in the broader healthcare sector, pharmaceutical companies show greater organizational readiness to scale AI. About 80% of pharma firms have formal AI governance committees, compared to 73% of payers and providers, reads the report. In addition, funding for AI is increasingly centralized, with just 20% of AI budgets in pharma allocated by innovation teams, as opposed to 60% in other healthcare organizations.

In Mexico, the broader adoption of technological innovations in the pharmaceutical industry hinges on the ongoing digital transformation of its operations. This transformation is necessary to improve efficiency across the value chain and ensure long-term competitiveness in a rapidly evolving market. Although the process is still in progress, several companies have already begun implementing advanced technologies. One example is Laboratorios Liomont, which is using AI to analyze tissue images with the goal of identifying disease patterns — such as those linked to cancer — with greater precision.