AI trends in pharma: How leaders gain competitive advantage
AI trends in pharma: How leaders gain competitive advantage
Publish Date: 2026-05-06 03:08:00
Source Domain: www.imd.org
Executive insights: AI for scaling, metrics, and transforming healthcare
Recent McKinsey & Company research suggests that while nearly eight in 10 companies report using generative AI, around 80 percent see no tangible bottom-line impact. The issue is not a lack of promising use cases, but rather the difficulty of scaling these beyond isolated pilots. According to industry executives, this issue is prevalent in the pharmaceutical industry.
Historically, AI has been deployed in isolated pockets within large multinational pharma firms, primarily in R&D, supply chain, and manufacturing, where machine learning is well established. With the advent of generative AI (GenAI), however, the barrier to entry has fallen significantly, enabling applications across a much broader range of activities. While this creates opportunities to bridge previously siloed use cases, it also introduces new challenges related to task interdependencies.
Ben Torben-Nielsen, Strategy and Portfolio Leader for Data Analytics and Insights at Roche, explains: “Most organizations focus on a handful of big AI use cases, but a typical workflow involves 20 to 50 tasks. I focus on embedding AI across as many of those as possible. Given the interdependence between tasks, optimizing just one rarely delivers a meaningful impact. Instead, I work on restructuring entire workflows, especially as some tasks may no longer be necessary with AI.”
In addition to scaling challenges, industry executives also highlighted a second issue: the current emphasis on efficiency and speed as the primary metrics for AI implementation. David Drodge, AI strategy and digital transformation at Roche/Novartis, argues that this focus is too narrow and risks overlooking AI’s broader potential for value creation. As he explains, “Current approaches to AI implementation often resemble a ‘rearview mirror’ view, focused on how things have been done in the past. Instead, pharma firms could leverage AI to build new…
