FEATURE
SCALING AGENTIC AI IN LIFE SCIENCES: MOVING BEYOND PILOT PROGRAMMES TO ENTERPRISE VALUE
As Generative AI matures in life sciences, many organisations struggle to scale beyond pilot programmes. Christopher Wooden, Sr. Director, Global Market Insights, and Charles Rink, Sr. Principal, Information Management & Analytics Technology at IQVIA, explore how agentic AI offers a path to enterprise value. They examine the challenges of adoption, the criteria for successful implementation and the strategic opportunities for commercial leaders looking to integrate intelligent systems into daily workflows for measurable business outcomes.
The use of Artificial Intelligence( AI) in life sciences has reached an inflection point. While Generative AI captured the initial attention of companies with impressive demonstrations and pilot programmes, the industry now confronts a sobering reality: more than 70 % of Generative AI experiments fail to scale and deliver meaningful business outcomes. This failure represents more of a challenge to find appropriate ways to strategically implement these programmes than a lack of technological capabilities.
The path forward does not mean abandoning these initiatives but instead means we must evolve basic generative models. Using agentic systems that can independently create content, make decisions, take actions and learn contextually would be more beneficial.
For commercial leaders, this evolution represents both the greatest opportunity and the most complex scaling challenge of the digital era.
The agentic advantage: Moving beyond generative to action
While generative models focus on creating humanlike output, agentic systems take the next critical step: autonomous action. These platforms do not just analyse data or generate reports; they execute tasks, apply reasoning and
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