Healthcare And Life Sciences: Turning AI Momentum Into Lasting Value
💡
Key Takeaway
Healthcare and life sciences firms are deploying AI faster than they are building the governance, data integration, and workflow infrastructure required to make it work – and clinical associations, regulators, and the FDA are already signaling that poorly implemented tools carry real consequences. The pattern mirrors what happened with electronic medical records and real-world evidence platforms: the technology was sound, but fragmented systems and weak adoption meant the promised value never materialized. Senior leaders approving AI budgets today should demand proof of enterprise-level governance and measurable outcome alignment before the next deployment – because retrofitting trust after the fact costs more than building it in from the start.
Healthcare and life sciences firms are deploying AI faster than they are building the governance, data integration, and workflow infrastructure required to make it work – and clinical associations, regulators, and the FDA are already signaling that poorly implemented tools carry real consequences. The pattern mirrors what happened with electronic medical records and real-world evidence platforms: the technology was sound, but fragmented systems and weak adoption meant the promised value never materialized. Senior leaders approving AI budgets today should demand proof of enterprise-level governance and measurable outcome alignment before the next deployment – because retrofitting trust after the fact costs more than building it in from the start.
Originally reported by Forrester Research Blogs. Read the full story here.
