Friday 23 May 2025 | 12:45–13:45

Format: In the round

Stream: Science

Content filters: Recommended for those working at system level in QI

Session chair: Amar Shah East London NHS Foundation Trust; England

PART ONE: Integrating artificial intelligence into your quality improvement approaches

This session is aimed at showing you how to start integrating artificial intelligence into the way that you teach and apply quality improvement in your organization.

We will begin by outlining the opportunities that generative AI offers, with live examples in the room to see the rapidity and accuracy of the tool. We will share examples from two healthcare systems that have already begun testing and learning how to integrate QI into quality improvement practice – supporting teams to use QI in theory building, harnessing the evidence base, developing measurement plans –even teaching and capability building offerings.

We will help attendees identify the key risks to be aware of with AI, and how we can mitigate against these.

By the end of this session, participants will be able to:

• Identify the opportunities to integrate artificial intelligence (AI) into the way that we teach and apply quality improvement


• Experience the power of AI to simplify and accelerate improvement work and contribute to teams.


• Develop practical approaches to mitigating the risks of AI

James Hoffman St Jude Children’s Research Hospital; USA

PART TWO: The promise and peril of AI in clinical care and population health

Dr. Weeks will provide an overview of Microsoft’s philanthropic AI for Good Research Lab, articulate how artificial intelligence has and can be used to care and health outcomes for patients and populations (particularly for the vulnerable and those living in resource-poor environments), and present guidelines for avoiding pitfalls of the use of AI in that work.

By the end of this session, participants will be able to:

• Summarise how AI can be used in clinical care and population health management


• Describe how AI can be integral to improvement efforts


• Explain how to avoid potential pitfalls in the use of AI in health and healthcare

William Weeks Microsoft; USA

PART THREE: To be announced