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Blog
Demetri Giannikopoulos

Why Change Management Is a Necessary Component of Successful AI Governance

Adoption, C-Suite, Care Coordination, Communication, Outcomes
Table of Contents

Often the focus of AI governance is crafting comprehensive policies and procedures to ensure patient safety and mitigate risks. While these are essential to AI implementation, health systems cannot overlook another critical component: change management. 

Simply defined, change management is the process that guides organizations through a transition, whether technological or operational. It involves planning, implementation and ongoing practices that affirm the change and improve performance. Effective change management minimizes disruption and ensures successful outcomes. 

It is also the bedrock of effective AI governance, serving as the bridge between policy and practice. Change management is the catalyst for building trust, because without buy-in and acceptance from clinical stakeholders, even the strongest governance framework will fail.

Sarah Kramer, MD, Clinical Associate Professor, Clinical Informatics at University of Nevada Reno School of Medicine and former CMIO, refers to change management and governance as building a “coalition” to ensure decisions aren’t made in a vacuum. 

She said:

Healthcare administrators can ‘kill physicians with kindness.’ They want to remove burdens from them and handle administrative tasks so physicians can stay at the bedside. The downside to that is sometimes the physicians feel like they are the last to learn about things, or they don’t get the full picture behind what is being done.

While not every stakeholder needs a formal role in AI governance, it’s crucial to involve clinical end-users early in the change management process. Empowering the clinical champion to voice frontline perspectives can proactively address potential concerns before rollout.

Build Change Management Into AI Governance

Effective change management drives behavior change through two-way dialogue and a clear plan. It involves aligning people with organizational goals, minimizing disruption and ensuring long-term success. 

The emphasis is on collaboration – involving employees so resistance is addressed and goals can be achieved. Change management will not be effective if it is viewed as a top-down mandate or is simply a PDF of rules linked on the intranet. 

Consider these change management strategies when establishing AI governance:

  • Baseline Your Current Process: Knowing and quantifying your existing process will allow you to better understand where you need to go.
  • Allow Engagement: Involve clinicians, administrators and patients in shaping AI initiatives at key stages to build a shared vision. Don’t shy away from open communication.
  • Empower Champions: Leverage their expertise and connections when drafting policies and procedures that will impact end-users.
  • Encourage Communication: Promote open dialogue about AI – what it does, how it will be used and safeguards in place – to build trust. 
  • Be Transparent: Be clear on how AI outcomes will be measured and usage will be monitored. Put this information in a place that is easily accessible to those that need to know.
  • Ongoing Education: Emphasize ongoing training aligned to metrics so skill and knowledge gaps are addressed. 
  • Celebrate Wins: Regularly share the impact of AI on patient outcomes, staff satisfaction and organizational performance.

By integrating change management principles into AI governance, healthcare organizations demonstrate that people are as important as process. Remember, AI is only a tool; it’s the people who use it and the environment in which it’s deployed that truly determine its impact. Explore more AI governance best practices.

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Demetri Giannikopoulos

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