The 2026 ASCO Annual Meeting (May 29–June 2, McCormick Place, Chicago, and online) will bring together the global oncology community to advance change in oncology practice and cancer care. This year’s program is built around the presidential theme of 2025–2026 ASCO President Eric J. Small, MD, FASCO: “The Science and Practice of Translation: Improving Cancer Outcomes Worldwide.”

Jo Chien, MD, Professor of Medicine at University of California, San Francisco, and Chair of the 2026 ASCO Annual Meeting Scientific Program Committee, explained that this theme is carried throughout both the scientific and educational programs in carefully chosen sessions that address larger issues as well as opportunities in oncology practice.

AI is one such area of opportunity in oncology practice in which new tools and technologies can complement and support the cancer care team while also expanding access in resource-limited settings. Through Education Sessions, Clinical Science Symposia, and oral and poster presentations, the ASCO Program Committees have embraced the potential of AI to transform global cancer care.

In this interview with ASCO AI in Oncology, Dr. Chien explains how AI is being addressed throughout the meeting to help oncology professionals better understand how to use these tools and technologies to improve practice and patient care.

Have you seen increased interest in AI surrounding the ASCO Annual Meeting, and how did the Scientific Program Committee approach incorporating AI into the program?

We are definitely seeing a rise in the number of AI-related abstracts submitted to ASCO so we had to be thoughtful about how to organize the content. We actually approached it in multiple ways. I think it's important to place abstracts where people will most easily find them, especially because attendees navigate the meeting in different ways.

If someone is interested in AI, they may search specifically for AI-related sessions regardless of where they appear in the program. But we also know that some attendees navigate the meeting by disease track and attend, for example, all the breast cancer sessions, which means they could miss an AI-related abstract presented in the Prevention track.

We wanted to make sure the research was reaching the people for whom it is most relevant. We also wanted authors to have a say in where they would like their AI-related research to appear. For that reason, we created an AI subcategory within each disease track during the abstract submission process.  We also added a checkbox for authors to indicate whether the abstract was associated with AI. That allows us to track whether the number of AI-related abstracts is increasing, where those abstracts are going, and how they are being categorized. However, this does not mean abstracts can’t be reassigned as we build out the sessions. 

For example, one of our Special Clinical Science Symposia this year is focused on AI.  These cross-disciplinary sessions highlight abstracts centered on a specific theme relevant to multiple disease tracks and fields.  They are also high-profile sessions within ASCO, and I wanted to include one focused on the use of AI in clinical decision-making—specifically, whether AI can be used for clinical decision-making, and how we validate its readiness for the clinic.

We selected four abstracts spanning different disease types that attempt to address these questions. We believe these sessions add tremendous value by bringing together people from different disciplines—data scientists, machine learning engineers, clinicians, and patients—to share ideas and perspectives that can inspire collaboration and innovation.

Were there any specific concerns that you and the committee had during planning regarding the rapid pace of AI development and how it might impact presentations?

We recognize that the field is changing and evolving very quickly. As in many areas of technology, there can be a natural tension between speed and safety.  We are seeing many studies using a variety of AI tools for clinical decision-making, whether for prognostication, identifying patients who may or may not benefit from treatment, or identifying those who may be at higher risk for side effects.

There are many AI tools emerging, and their use will require rigorous external validation. We believe it is important to present AI-related studies as the field evolves, even if they are not ready for prime time, as long as the methods and scientific rigor are sound. As with all abstracts, we rely on our expert discussants to place the research in context and identify where the data may not be ready yet for clinical use.

Is there anything you would like to see more of in the AI-related abstracts being submitted?  

I’d love to see more AI-related abstracts that move beyond proof-of-concept and focus on real-world clinical utility. We’re seeing many abstracts focused on model performance in prognostication, diagnostics, and prediction.  The natural next step is to validate these tools prospectively to determine whether they actually improve patient outcomes and clinical decision-making. 

I’d also like to see more abstracts on how AI use impacts providers and clinic operations. As more AI tools enter the clinic, it will be important to assess their impact on physician burnout, documentation, scheduling, and clinical trial enrollment. 

Finally, I believe, and hope, that AI will make high-quality oncology care more accessible. It would be interesting to see its impact on patient education, symptom monitoring, and remote care, as well as whether it helps reduce disparities in underserved populations.

For someone who is newer to AI in oncology, where would you recommend they start at the ASCO Annual Meeting?

There are many different ways to access AI-related content at the meeting. One straightforward approach is to search for “Artificial Intelligence” in the online program, which will pull up all AI-related sessions and talks. 

I’d specifically like to highlight one of the Special Clinical Science Symposia, “From Data to Decisions: Applying Artificial Intelligence for Smarter, More Accessible Cancer Care.” This session will feature several abstracts using AI to address clinically relevant unmet needs. 

There is also a Clinical Science Symposium in the Medical Education track focused on optimizing AI use for patients, providers, and trainees in the clinic. In addition, an education session in the Prevention, Risk Reduction, Genetics, and Global Health track is specifically dedicated to scalable AI and digital tools for resource-limited settings.

For live AI-related coverage from the 2026 ASCO Annual Meeting, visit ascoai.org/meetings/. 

ASCO AI in Oncology is published by Conexiant under a license arrangement with the American Society of Clinical Oncology, Inc. (ASCO^®). The ideas and opinions expressed in ASCO AI in Oncology do not necessarily reflect those of Conexiant or ASCO. For more information, see Policies.