Generative AI can potentially revolutionize the life sciences industry, driving innovation across key areas of the value chain. By streamlining drug discovery, optimizing clinical trials, and enhancing decision-making, it can significantly reduce the time and cost required to bring new medicines to market, setting a new benchmark for industry efficiency and innovation. However, adopting generative AI presents challenges including concerns about data privacy, model accuracy, training resource demands, and ethical implications.
As providers work toward addressing these challenges and generative AI becomes a key industry innovation driver, the focus is slowly moving beyond experimental pilot projects to full-scale implementations.
This report examines generative AI’s value promise across the life sciences value chain, its market adoption within the industry, and the capabilities of 15 leading providers driving this innovation from pilots to scaled deployment.
Scope
Industry: life sciences
Geography: global
The assessment is based on Everest Group’s annual RFI process for the calendar year 2024, interactions with leading life sciences providers, client references, and Everest Group’s ongoing analysis of the life sciences market
Contents
In this report, we examine
Generative AI’s value promise across different segments of the life sciences value chain
