Healthcare and life sciences (HCL) firms are moving fast on AI — much faster than expected. But so are consumers. From domain-specific AI tools to enterprisewide ambient technology integration, accelerating drug discovery, and connecting medical records and health apps for a more personalized experience, the momentum is real. The promise is also real: AI is the foundational capability for building the intelligent healthcare organization (IHO) and delivering better experiences for consumers, employees, and the business. But speed without strategy is emerging as the dominant risk.
We’ve seen this play before. Technologies such as electronic medical records, real-world evidence platforms, and chatbots were expected to produce tangible value, but most fell short of expectations. The issue wasn’t the technology itself. It was fragmented data, weak integration into workflows, and limited front-line adoption. If HCL firms take the same approach with AI and deploy workforce and consumer tools without fixing these underlying issues, they are sure to repeat the cycle and struggle to realize measurable value.
Listen To The Warnings About Rapid AI Deployments
As investment accelerates and leaders acknowledge that AI is necessary to achieve IHO ambitions, many firms still approach AI as a series of pilots, point solutions, and bolt-ons. Without addressing governance, integration, and workforce readiness up front, HCL orgs run the risk of a “trust tax” (the cost of retrofitting these capabilities after deployment). This will create lasting operational friction and experience hurdles. As a result, consumers, industry leaders, and professional orgs are raising red flags:
Clinical associations such as the American Medical Association, American Nurses Association, and the American Academy of Nursing are questioning how AI is being deployed, how it affects workload, and whether it can be trusted in high-stakes environments.
The National Association of Insurance Commissioners is actively exploring new regulation and modeling laws for AI governance and consumer protection.
The FDA recently released a warning letter alerting life science orgs to the risks of using and advising against overreliance on AI in drug manufacturing. This isn’t resistance to AI. It’s resistance to poorly implemented technology and the perils that come with it.
At the same time, big tech and new entrants are rapidly defining what good AI experiences look like, often outside of traditional HCL orgs. This creates an unbalanced environment where HCL firms risk losing influence over both workforce and consumer experiences. AI may be a necessary foundation for the IHO, but necessity does not eliminate the need for discipline and strategy.
Align Tech With Measurable Outcomes To Avoid The Trust Tax
HCL leaders must move beyond rapid AI experimentation and commit to enterprise-level strategy, governance, and workflow redesign or risk repeating the shortfalls of past digital investments. Previous technologies failed to deliver not because of capability but because they were layered onto fragmented systems without rethinking how work gets done. AI will be different only if HCL firms proactively define standards, align technology to measurable outcomes, and create governance for end-to-end deployments from the start. Taking this approach and acting with discipline will reshape care delivery, build trust, and define the next generation of AI-driven experiences.
Our upcoming reports on consumer-facing AI in healthcare and the impact of AI on the HCL workforce will explore the impact of AI on both the customer and employee experience. They also explore optimal design and address how leaders can scale adoption in ways that drive value, not just engagement.
Forrester clients can schedule a guidance session with me to discuss how their organization can prepare for consumer-facing AI and the impact of AI on the workforce. Not yet a Forrester client? Contact our sales team to learn about Forrester Decisions and how we can support your organization.
