Building Scalable, Responsible AI Systems in Regulated Industries
Scalable AI systems require a strong foundation. Data, engineering, platforms, operating models, and governance must work together to support responsible implementation and long-term value.
In this session from MIT Technology Review’s EmTech Future conference, Jing Wang of Vanguard explores what it takes to build that foundation in a highly regulated environment. The discussion examines how reliable, responsible AI implementation can help organizations turn emerging capabilities, including agent systems, into lasting value for investors.
About the speaker
Jing Wang, Principal, AI and Insights Center, Vanguard
Jing Wang leads Vanguard’s Center for AI & Insights (CAI), driving the company’s artificial intelligence, machine learning, generative AI, and behavioral science capabilities. Her team leads innovation, research, and delivery across the company, helping Vanguard transform emerging technologies into trusted solutions, improve customer experiences, strengthen investor outcomes, and create measurable business value.
Prior to her current role, Wang held leadership positions in Vanguard’s Financial Services, Workplace Solutions, International, and Corporate Services divisions. Throughout her tenure, she has led team and company initiatives that support strategic priorities, strengthen customer outcomes, and improve overall company performance.
Wang joined Vanguard in 2009 after several years as a principal at Boston Consulting Group. She received a bachelor’s degree in physics from the University of Science and Technology of China and a Ph.D. She also holds a BA from the University of Pennsylvania and an MBA in Finance and Marketing from the Wharton School of Business at the University of Pennsylvania. Wang holds Series 7, 24, and 65 licenses.
Source: www.technologyreview.com