The data leader's role has shifted from running data operations to enabling the business across data and AI, yet many firms are jumping into AI tools before building the workforce capability to use them. As AI moves to CTOs, CAIOs and business lines, it is often unclear who is accountable for its business results. Panelists share how they anchor AI to business objectives and the risk framework, build capability across the workforce and assign clear ownership for results.

• Build data and AI capability across the workforce before buying more tools
• Assign clear accountability for the revenue, cost and risk outcomes of AI across data, technology and business leaders
• Anchor AI strategy to business objectives and the enterprise risk framework, with governance built into the platform

Co-facilitated with CIO/CTO TBC

At most institutions, the CDO or CDAO, the Chief AI Officer, the CIO and the CTO each own part of the AI agenda, and the gaps between them are where programs stall and budgets get duplicated. This off-the-record boardroom brings executives together to work out who owns what: data, models, platforms, infrastructure and risk. It also covers how to fund and govern that work as one program heading into 2028.

• Agree which role owns data, models, platforms and agent risk, and where decision rights overlap
• Build a joint funding case that protects foundational data and infrastructure spend alongside AI results
• Set shared metrics and a joint roadmap so every role answers the same question from the board