Vanguard 如何构建可扩展 AI 的基础
The Foundations of Scalable AI
Vanguard 智能与洞察中心的 Jing Wang 在 MIT Technology Review 的 EmTech Future 会议上分享如何构建可扩展 AI 系统的基础，涵盖数据、工程、平台、运营模式与治理的融合。她探讨了在高度监管环境中落地负责任、可信赖的 AI，包括 agentic 系统等新兴能力，将其转化为投资者的持久价值。
A scalable AI system requires a strong foundation. Data, engineering, platforms, operating models, and governance must converge to work as one. This session from MIT Technology Review's EmTech Future conference explores what it takes to build that foundation in a highly regulated environment and how a responsible, trustworthy implementation can turn emerging capabilities, including agentic systems, into lasting value for investors.
About the speaker
Jing Wang, Principal, Center for AI and Insights, Vanguard
Jing Wang leads Vanguard's Center for AI & Insights (CAI), advancing the firm's AI, machine learning, generative AI, and behavioral science capabilities. Her team drives enterprise-wide innovation, research, and delivery, enabling Vanguard to translate emerging technologies into trusted solutions that enhance client experiences, improve investor outcomes, and create measurable business value.
Before her current position, Jing served in a range of leadership roles across Vanguard's Financial Services, Workplace Solutions, International, and Corporate Services divisions. Throughout her tenure, she has led teams and enterprise initiatives that advanced strategic priorities, strengthened client outcomes, and drove business performance across the firm.
She joined Vanguard in 2009 after several years as a Principal at the Boston Consulting Group. Jing earned a B.S. in Physics from the University of Science and Technology of China, a Ph.D. from the University of Pennsylvania, and an M.B.A. in Finance and Marketing from the Wharton School of Business at the University of Pennsylvania. Jing holds Series 7, 24, and 65 licenses.
来源： MIT Technology Review · AI · technologyreview.com