Healthcare has a history of using technology to do a heroic amount of work. Electronic health records (EHRs) were supposed to centralize patient data, patient portals were supposed to simplify access, automation was supposed to make operations hum: Much of that didn’t happen — at least not as neatly as demos promised. And now AI has entered the discussion. Across healthcare organizations (HCOs), AI is pushing leaders to rethink what work should look like.  

But leaders should resist treating AI like an Easy button. The industry can’t automate its way out of workforce shortages. AI’s value depends on how well it strengthens human judgment, trust, and care delivery. 

Workforce Readiness Is Becoming The Real AI Bottleneck 

Healthcare leaders are moving fast on AI, but many are moving faster on tools than on their people. This gap is risky and already visible: 80% of health insurers AI leaders say nontechnical employees understand how to use AI responsibly and ethically, yet only 42% of employees report confidence around ethical AI use. Realizing AI value depends less on whether HCOs deploy AI and more on whether they redesign work, build workforce readiness, and close trust gaps between leaders and staff.  

But this should feel familiar. EHR modernization taught the industry that technology adoption isn’t the same as workflow transformation. A tool can “go live” while clinicians still experience it as one more burden, click, alert, or workaround. That pattern will repeat at greater speed if HCOs don’t treat AI adoption as a workforce reinvention effort. Our research shows that the industry will continue to add jobs as AI deploys. Redesigning work will only become more urgent as genAI’s influence on healthcare roles rises from 4% in 2025 to 30% by 2031. 

Four Steps To Make AI A Workforce Advantage 

Leaders need to be more deliberate about where and how AI changes work. Use these four steps to focus on making AI a practical advantage for the people delivering, supporting, and financing healthcare: 

  1. Create an “AI friction log” before scaling use cases. Instead of starting with the biggest AI use case, leaders should ask the workforce to document the moments where work slows down, fails, loops, or creates avoidable frustration. This gives leaders a better way to prioritize friction-removed, rather than hype-generated, investments. 
  2. Put staff in the AI product-manager seat.  Employees need to be treated as co-designers who shape AI. This creates a more grounded version of governance and brings clarity around how decisions are made. 
  3. Build moments of trust into every AI-enabled workflow. Trust in AI will be earned in small moments: when a claims professional sees why medical codes were extracted, when a contact center agent can override a suggested response, or when a patient knows a clinician reviewed an AI-generated summary. HCOs should design these trust moments intentionally. 
  4. Stop funding pilots without an exit ramp. Healthcare is littered with pilots that never end, never scale, and never admit defeat. HCOs need a more disciplined model: Every AI pilot should have a front door and an exit ramp. 

Turn AI Momentum Into Practical Workforce Reinvention 

Healthcare doesn’t need another technology optimism cycle that ends with disappointed employees and underwhelming ROI. It needs practical workforce reinvention, which will enable AI to help HCOs expand capacity, reduce burden, and redesign work for the future. Checkout my latest report, Healthcare Workforce Reinvention, and my upcoming report, US Healthcare AI Job Impact Forecast, 2025 To 2031, for a deeper look at how AI will reshape healthcare work, which roles face the greatest disruption, and what HCOs should do now to build an AI-ready workforce.  Forrester clients should: 

  • Schedule a guidance session to dig deeper into the research and what it means for your business and customers. 
  • Consider a deeper dive via a strategy session. 

If you’re not a Forrester client, reach out to our sales team! 

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