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Live from Stanford Health AI Week

Stanford Online9 July 2026Watch on YouTube

Part of series

Ep. 12 · 2026 Ai4mh Health

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Description

Learn more about Stanford's online Healthcare AI programs: https://online.stanford.edu/artificial-intelligence/ai-professionals-healthcare Check out the AI in Healthcare series playlist: https://stanford.io/3NEt7uE Matt Lungren, Stanford University - https://profiles.stanford.edu/matthew-lungren Justin Norden, Stanford University - https://med.stanford.edu/profiles/justin-norden Recorded on location at Stanford Medicine’s Health AI Week, Matt Lungren and Justin Norden sit down with leaders from healthcare, life sciences, and industry to separate hype from progress in medical AI. Together, they explore where AI is already improving day-to-day work, from surfacing the right information at the right time to making tools that feel practical for clinicians and staff. The guests also dig into what it will take to prove impact at scale, including how organizations should measure outcomes, manage change, and fund the most promising use cases. The episode closes with a look at how AI could reshape research and clinical trials and what responsible adoption should prioritize. 5 key points: 1. AI’s biggest impact is already showing up at the patient level through improved access to knowledge and information. 2. Measuring impact is the central challenge: how to quantify quality and outcomes improvements at a national scale. 3. Evidence still matters: the “survival curve” moment is powerful, but it must be followed by proof, validation, and deployment planning. 4. Research and clinical trials are poised for change: identifying and enrolling participants and running studies will look different. 5. Workforce and culture are diverging sharply: leaders debate automation vs. job-loss narratives, and organizations are taking very different approaches to adopting AI tools. Stanford Online, in collaboration with the Stanford Center for Health Education, is brought to you by the Stanford Engineering Center for Global & Online Education.

What you'll learn

  • AI in healthcare is already showing impact at the patient level through improved access to knowledge and information.
  • Measuring impact is the central challenge: quantifying quality and outcome improvements at a national scale.
  • Research and clinical trials will change, with different approaches to participant identification, enrollment, and study execution.
  • AI tools must feel practical for clinicians and staff, with a focus on surfacing information at the right time.
  • Organizations are taking diverging approaches to AI adoption, creating sharp differences in workforce and organizational culture.

Frequently asked questions

Where is AI already showing impact in healthcare?
AI is already showing impact at the patient level by improving access to knowledge and information. It helps clinicians surface the right information at the right time, improving daily work.
What is the biggest challenge in proving AI impact in healthcare?
Measuring impact at scale is the central challenge. Organizations must prove how AI improves quality and outcomes, and this must be followed by validation and deployment planning at a national level.
How will research and clinical trials change because of AI?
AI will change how participants are identified and enrolled, and how studies are conducted. This opens opportunities for more efficient and effective study design.
What matters in responsible AI adoption in healthcare organizations?
Responsible adoption should prioritize practical tools clinicians can use, with attention to workforce impact and organizational culture. However, different organizations are taking very different approaches.

Topics

healthcare aiclinical applicationsimpact measurementresearch & trialsworkforce