A study released by Google Cloud late last year offered some eye-opening insights into where life sciences and healthcare executives are using artificial intelligence (AI), where they are not, and most importantly, where they are finding a return on investment (ROI) from their AI spending. For years, drug developers have long cited drug development purposes as key reasons for using AI—such as finding challenging drug targets, training large language models for drug discovery, facilitating biomanufacturing, and slashing the time and expense of R&D. Shweta ManiarGlobal Director, Life Sciences Strategy & SolutionsGoogle Cloud However, Google Cloud’s report, The ROI of AI in Healthcare and Life Sciences, found “productivity and research” to be only the second most frequent purpose for using AI agents at 39% of executives surveyed. Marketing led the list of purposes with 41% of execs surveyed, tied for the top percentage with tech support. (Respondents could list multiple uses.) Marketing finished second, though, in generating ROI from agentic AI, with 27% of executives citing that activity compared with 28% citing product innovation and design. Automated document processing was third at 26%. “This mix of broad and industry-specific use cases sets the life sciences industry apart from other industries—and shows how the most substantial ROI opportunities for the life sciences industry lie in core business functions,” observed Google Cloud, which provides AI as well as cloud computing services. Adopting agentic AI for core life sciences processes such as quality control (done by 37% of respondents), automated document processing (36%), and…
