CAIT and how AI can support performance improvement

About this Session

In this presentation, we will begin with an introduction to ISPI’s AI4PI Framework and the application processes for CAIT and the AI4PI Award, both of which use the same rubric. To answer the question of how AI can support PI, we will help participants develop a practical way to think about AI in their own domains. Participants will gain a high-level understanding of what generative AI is and how language models work. Using concrete examples as a starting point, we will discuss the professional “moat” PI practitioners can build around data, methodology, professional judgment, and human touch. These ideas will be connected back to the four principles and six implementation steps of ISPI’s AI4PI Framework.

About the Speakers

Frank Q. Fu, CPT, PhD, is an ISPI board member, Director of Certification, and an associate professor of marketing at the University of Missouri - St. Louis. He has published articles in major marketing journals and presented at national and international academic conferences. His work has appeared in the Journal of Marketing, Journal of Personal Selling & Sales Management, Human Performance, and Performance Improvement. He currently serves on the Editorial Review Board of the Journal of Marketing Theory & Practice and coauthored the book ROI in Marketing: The Design Thinking Approach to Measure, Prove, and Improve the Value of Marketing. Prior to joining academia, he gained sales, marketing, and management experience in the pharmaceutical and medical equipment industries. In addition to academic research and teaching, he helps American and Chinese companies improve their business performance through consulting and advising efforts. He may be reached at fuf@umsystem.edu.

Kevin Z. Fu is a Master of Science in Computer Science candidate at the University of Chicago, specializing in AI Systems and Data Analytics, with research centered on knowledge and memory systems for AI agents. He serves as a Graduate Research Assistant at the Pritzker School of Molecular Engineering, where he develops AI systems for autonomous, closed-loop scientific experimentation. Alongside his research, Kevin advises academic researchers and business professionals as an independent AI consultant on AI strategy, adoption, and risk. He brings prior industry experience as a Software Engineer at IMC Trading and holds a Bachelor of Science in Computer Science from Washington University in St. Louis. He may be reached at kevinfu@uchicago.edu.

Accessibility

Live captions available. All registrants will receive the session recording and resources.