From MIT Technology Review · · 50s
Building AI systems that scale responsibly
Scalable AI requires data, engineering, platforms, operating models and governance working together in regulated environments.
In brief
Scalable AI requires data, engineering, platforms, operating models and governance working together in regulated environments. MIT Technology Review's EmTech Future conference explored how to build scalable AI foundations that deliver lasting value while operating responsibly in regulated sectors. Originally reported…
Five foundations for scalable AI
Data, engineering, platforms, operating models, and governance must converge to work as one. MIT Technology Review's EmTech Future conference explored building these foundations in regulated environments.
“A scalable AI system requires a strong foundation.”
Jing Wang leads Vanguard's AI centre
Jing Wang, Principal at Vanguard's Center for AI and Insights, drives enterprise-wide innovation translating emerging technologies into trusted solutions that enhance client experiences and improve investor outcomes.
Responsible implementation creates lasting value
A responsible, trustworthy implementation of emerging capabilities, including agentic systems, can turn AI into lasting value for investors while operating in highly regulated environments.
The key point
MIT Technology Review's EmTech Future conference explored how to build scalable AI foundations that deliver lasting value while operating responsibly in regulated sectors.
