The best unit of measure to quantify ROI in the healthcare and life sciences domain is process transformation, not isolated use cases.
AI in healthcare and life sciences is no longer about ‘if’ but ‘how to scale with real ROI’. Yet many organizations remain stuck in the use case trap, focusing on isolated pilots that show quick wins but fail to scale due to a lack of integration with broader processes and service delivery. The highest ROI doesn’t come from standalone AI use cases but from embedding AI into end-to-end processes, where it drives cost savings, faster care, and improved quality over a 3–5-year horizon.
The use case trap arises when organizations optimize single tasks, like prior authorization or clinical documentation, without accounting for system dependencies, clinician adoption, or downstream workflows. This approach often leads to pilot purgatory, where small wins fail to translate into enterprise value. Instead, leading organizations achieve sustainable ROI by starting with strategic service delivery goals, transforming end-to-end processes, and embedding AI where it adds the most value.
The key to escaping the use case trap is reframing AI ROI around process transformation. Use cases are the entry point, processes are the unit of measure, and service delivery is the ultimate outcome. By shifting to relevancy-driven AI, HLS organizations can unlock enterprise-level ROI and transform care at scale.
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