Leigh Felton

President and Chair

AI for Job Security Foundation

Enterprise AI strategy has matured. Use cases are defined, data architectures are built, governance frameworks are deployed, and change management programs are scaling. Most of that progress is built on an assumption that is no longer holding: that AI functions as a tool, which can be evaluated at the point of use.

Many deployed AI systems are doing something different. They are shaping how decisions get made, how performance gets measured, and how opportunity gets distributed across the organization. That shift creates a structural gap that existing strategic frameworks cannot resolve, because the gap is in how those frameworks define the problem itself.

This session gives enterprise leaders a different lens for thinking about value, skills, and change management when the systems they have deployed are no longer just supporting work, but beginning to define the conditions under which work happens. Participants examine where current AI strategy frameworks are calibrated for a category of system that their deployed AI has already outgrown, what that means for how value is actually being created and lost, and what workforce and change management approaches hold when AI systems shape the environment rather than simply produce outputs within it.

The session draws on direct experience leading responsible AI strategy at enterprise scale and translates that experience into practical diagnostic questions participants can apply to programs already in motion.

You Will Learn

• Why AI strategy frameworks calibrated for tool-based systems produce structural blind spots when applied to deployed AI that shapes decisions and conditions
• How to identify where your enterprise AI programs are generating value and costs that current strategy metrics are not capturing
• How the shift from AI as output producer to AI as environmental condition changes what skills development must prioritize
• Why change management approaches built on adoption curves fail when the system being adopted is also reshaping the work itself
• How to translate these structural shifts into strategy decisions your leadership team can act on now

Geared To

• Enterprise AI strategy leaders and program owners
• Chief data officers and chief AI officers
• Organizational change management leaders working with AI programs
• Business stakeholders responsible for AI value realization
• HR and workforce development leaders designing AI skills programs
• Data and analytics leaders managing the gap between AI delivery and sustained business impact