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Blog
Andy Pollen

The Hidden Hero of Clinical AI: Change Management

Adoption, Change Management, Workflow
Table of Contents

Picture this: You buy an amazing AI platform for your health system. You’ve invested time and financial resources into making the decision, and you’re confident it’s the right thing for your organization.

While you fully believe in the value it can provide patients, providers and your bottom line, the tool isn’t being used – wasting your investment and diminishing the potential benefits for all involved.

Technology alone doesn’t transform care. People do. And real adoption takes more than a go-live date — it requires a deliberate strategy to empower champions, engage users, align workflows and measure success. 

That’s why Aidoc developed a comprehensive AI adoption and change management framework, drawing from best practices in healthcare transformation.

Here’s what we’ve learned from the systems that succeed:

  • Start with a structured methodology like PDSA (Plan–Do–Study–Act) or PDCA (Plan–Do–Check–Act) to create a repeatable framework for implementation, evaluation and improvement.
  • Map current workflows before introducing new tools. Use gap analysis to understand where AI will enhance care and where changes may create friction.
  • Engage the right champions early — ideally mid-level leaders who understand frontline challenges but have influence across teams.
  • Customize training by role and setting — from radiologists at PACS workstations to Emergency Department (ED) teams at the bedside — and use local champions to reinforce the rollout.
  • Track both objective and subjective metrics to monitor adoption and outcomes. Treatment times, user engagement, satisfaction and workflow impact all matter.
  • Communicate relentlessly. Reinforce project goals, map key audiences, and create a tactical outreach plan that addresses questions, sets expectations and builds confidence.

aiOS™ was built with this reality in mind. It embeds AI insights directly into native workflows, tailors experiences for different users and supports ongoing training, monitoring and improvement. We work hand-in-hand with clinical and operational teams — not just to deploy AI, but to make it work in the real world.

Because successful AI isn’t a product launch, it’s an organizational shift, and change management is what makes it real — and lasting. Find more considerations for driving clinical AI adoption and change management in this resource guide.

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Andy Pollen
Andy Pollen is a former Aidocee.
Andy Pollen
Director, Marketing Communications

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