NEW YORK — February 12, 2024— The generative artificial intelligence (AI) transformation is well underway in pharma, and pharma companies have high confidence in its value. Already, 40% of executives say they are baking expected savings into their 2024 budget, and 60% have set targets for cost savings or productivity boosts, according to a recent Bain & Company survey.
Nearly 60% of executives say that they have moved beyond ideation and brainstorming to building out use cases, with 55% reporting they expect to have multiple proof-of-concept or minimum viable product builds by the end of 2023.
“Over the next six to twelve months, leading companies will move from cultivating isolated pilots to scaling for results,” said Eric Berger, a partner in Bain & Company’s Healthcare & Life Sciences practice. “As leadership teams move beyond experimentation into pilots and launches, they are thinking carefully about when and how to communicate their AI journeys to investors. Those that can signal a structured, scalable enterprise-wide program, rather than a smattering of standalone initiatives, will reap the rewards in the next phase of AI.”
Data science and machine learning are not new to pharma executives who have been investing in productivity enhancements for years, primarily in the drug discovery space. Bain research shows 54% of pharma companies have automated biomedical literature review solutions, and 46% are using AI as part of their process to find potential disease targets. Now, generative AI is broadening the aperture of use cases with new opportunities across the value chain. Biomedical literature review and preclinical research remain among the most popular use case areas, although we’re also seeing high investment in IT and competitive intelligence. Within these top areas, more than 60% of executives say they have at least a proof of concept in development, and around 10% have already rolled out tools. These early adopters have moved swiftly, often reaching a working pilot within about eight weeks. Already, many are seeing tangible value.
Generative AI is top of mind for most pharma companies, with 75% citing it as a C-suite and board priority. And investors are watching closely to differentiate the pioneers from the followers. If pharma companies want to generate value from generative AI as fast as the technology allows, they need to ensure the organization is ready. Companies can take a three-tiered approach to prime their operating model for generative AI at scale:
- Determine your strategic posture. Leading organizations will establish decision-making and funding models that prioritize high-return use cases, ensuring that those use cases fit within their investment themes around bold bets for the future of the business.
- Lead through change. Generative AI at scale requires strong internal leadership and cross-functional alignment. The best companies will establish an organizational center of gravity with several executives who act as generative AI champions.
- Build the foundations. In addition to the right technology, data, and models, generative AI at scale requires reorienting the organization to support big visions. This includes recruiting aggressively for data scientists to work on AI initiatives, building strategic partnerships with external vendors for support, and thoughtfully engaging on ethics and regulation by going a step further with a companywide risk management approach.
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