Portugal Colonial - New Pharma AI Findings Reveal the Real Barrier to Scale: Execution, Not Innovation

Nearly 60% of respondents say their AI strategy lacks clear ownership, highlighting a gap between leadership ambition and operational accountability. Without defined business ownership and success metrics, many companies remain stuck between experimentation and scaled delivery.

Data is another barrier. According to the research, 67.3% of pharma leaders report fragmented or only partly reliable data. In a sector where commercial, medical, regulatory, and patient data often sit in disconnected systems, poor data quality can delay decisions, reduce trust, and weaken AI performance.

Many AI initiatives are still not aligned with the needs of end users. More than half of respondents report inconsistent user involvement in AI design, while 14.3% say a technology-first approach still dominates. In pharma, success depends on whether AI supports real-world decisions across medical, commercial, and market access functions.

"Pharma has already moved past the stage where AI is only a question of interest or innovation signaling," said Wiktor Fido, General Manager EMEA at Lingaro. "The organizations that will pull ahead are those that treat AI as an operating model challenge, not just a technology one. That means ownership, data discipline, and adopting AI into daily decisions from day one".

The research highlights how difficult that transition remains. More than three in four respondents (76.5%) say they are still between proof of concept and scalable production, suggesting that many companies have not yet put in place the governance, delivery methods, and infrastructure needed to scale successfully. At the same time, 64.3% say that AI is not yet embedded in day-to-day workflows and decisions, with adoption and change management cited as the top barrier to progress by 31.6% of respondents.

"One of the clearest signals in the data is that adoption is still underestimated," said Ivanka Vankova, Life Sciences Lead, Commercial Analytics at Lingaro. "Training matters, but it does not replace integration. AI creates value when it is built into the platforms, workflows, and role-specific decisions that shape daily work."

The full report: The State of AI Readiness in Pharma.

About Lingaro: Lingaro is an end-to-end Data & AI partner for Fortune 500 companies and global brands. Lingaro supports companies in designing, building, and adopting technology solutions that deliver real business impact, providing 24/7 support across three continents.

https://lingarogroup.com

Contact: [email protected]

SOURCE: Lingaro

View the original press release on ACCESS Newswire

P.Serra--PC