The Foundations of Scalable AI
Jing Wang, head of Vanguard's Center for AI & Insights, discusses the necessity of integrating data, engineering, and governance to build scalable AI systems. The session emphasizes the importance of responsible implementation in highly regulated financial environments.
Why it matters
As financial institutions adopt generative AI, establishing robust frameworks for trust and compliance is critical for long-term business value and investor protection.
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.
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.
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