The Responsible AI Institute (RAI) appointed Avivah Litan, Cameron Davies and Suraj Srinivasan to its Governing Board on Monday, adding expertise in AI risk and security, enterprise-scale deployment, and corporate accountability as organizations shift toward autonomous systems. The appointments signal a response to a structural change in enterprise AI: systems are moving from generating recommendations to planning, using tools and taking actions across business environments.
"AI is crossing a threshold from systems that primarily advise people to systems that increasingly act on their behalf," said Manoj Saxena, Founder and Executive Chairman of the Responsible AI Institute. "That makes responsible AI a board-level and operating-model issue, not simply a technology or compliance function."
Three appointments across risk, scale and accountability
Avivah Litan spent more than two decades at Gartner Research as Vice President and Distinguished Analyst, shaping the firm's work on AI trust, risk and security alongside research in fraud prevention and identity. Her appointment addresses a risk landscape expanding beyond traditional cybersecurity. Increasingly autonomous systems introduce questions around delegated authority, permissions and whether organizations can demonstrate that AI remains within defined limits.
"Agentic AI changes the risk equation because these systems do more than generate content. They can make decisions and take actions across enterprise environments," Litan said. "Organizations need practical ways to define what these systems are allowed to do, establish enforceable boundaries and independently verify that those controls are working."
Cameron J. Davies, Chief Data & AI Officer at Yum! Brands, leads the company's global AI, data and analytics organization supporting KFC, Taco Bell and The Habit Burger Grill. His perspective reflects a challenge enterprises face across industries: the difficulty is no longer identifying AI use cases but creating the architecture and operating model to deploy AI consistently across large organizations. "Most organizations aren't struggling to find AI use cases. They are struggling to create the operating model that allows hundreds or thousands of AI-enabled capabilities to be deployed consistently across the enterprise," Davies said. He added that trust is becoming a strategic advantage: "Responsible AI isn't separate from innovation; it is what allows innovation to scale."
Professor Suraj Srinivasan is the Philip J. Stomberg Professor of Business Administration at Harvard Business School, where his work spans artificial intelligence, corporate governance and board effectiveness. His research examines how Generative AI and LLM technologies change business performance and executive leadership. "AI is a strategic and organizational issue, not simply a technology issue. Boards need to understand both the opportunities these systems create and the new forms of risk, authority, and accountability questions they introduce," Srinivasan said.
From principles to verifiable proof
The expanded board comes as RAI grows its work on independent assessment of autonomous AI systems. Through initiatives including TrustX, the institute is developing approaches to classify AI risk based on factors such as autonomy and authority, establish proportional controls, and produce evidence that executives, boards, customers and regulators can use to evaluate whether AI systems operate within defined boundaries. RAI is applying this work through sector-focused initiatives in financial services and healthcare.
"The next generation of responsible AI has to connect technology, risk, enterprise operations and board accountability," Saxena said. "These appointments significantly strengthen RAI's ability to convene those perspectives and help organizations navigate what comes next."
Why this matters for executives and strategy leaders
The appointments reflect a shift in how organizations must think about AI governance. When systems move from advising to acting, oversight becomes a fiduciary concern, not a technical one. For executives and board members, the practical question is no longer whether to adopt AI but whether the organization can demonstrate - with credible evidence - that its systems stay within defined limits. RAI's focus on independent assurance and risk classification offers a framework for answering that question as AI for Executives & Strategy moves from policy documents to operating reality.
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