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Here is why it is SO hard to integrate AI in healthcare.

  • Writer: Angelina Chigrinetc
    Angelina Chigrinetc
  • Dec 21, 2025
  • 2 min read

by Angelina Chigrinetc

Angelina is an AI and Backend software engineer with 7 years of experience in healthcare and a Master's in Healthcare Management (SDA Bocconi).


And no — it’s not because of privacy concerns that sometimes make it impossible to use standard LLM APIs.

(Local models have gotten sooo much better.)


Introducing AI into real clinic operations is hard because:

There is no mission-led roadmap


Leaders often launch AI pilots without clearly tying them to business outcomes.

There’s no clear answer to:


  • What cost are we reducing?

  • What patient experience are we improving?

  • Which KPI must move?


AI then becomes a cool experiment for the press release or the CEO's ego instead of an actual profitability lever.


AI stays stuck in pilot mode


Scaling from PoC to production is easier said than done.


AI agents and workflows running in sandboxed environments must prove their usefulness and accuracy before being trusted with real operations — and often, they don’t meet the bar.


Legacy systems block impact


Most healthcare organizations still run on fragmented, outdated infrastructure:


  • old call-center tools 

  • rigid planning systems

  • brittle integrations


Plugging in a new AI service assumes flexibility that simply isn’t there sometimes.



Data is messy and fragmented


I will not tire of repeating this: AI without clean, cross-linked data is a shiny candy wrapper without the candy.


Looks promising. Completely useless underneath.


The operating model doesn’t change


The worst scenario? AI insights are produced — and then quietly ignored.

Why?

Because workflows, roles, incentives, and decision-making dynamics stay exactly the same.

If humans don’t trust, understand, or know how to act on AI outputs, value never materializes.



That's why it is so crucial to have a thoughtful, systematic and strategic approach to adopting AI, so that it fulfills on its promise of a powerful profit driver, not another shiny toy rotting in the wasteland of abandoned pilots.


 
 
 

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