January 27 | 11am - 12pm PT or 2pm - 3pm ET 

You have made the AI investment. The tools are live, the pilots have run, and the utilization dashboards look healthy. Now you’re planning the year ahead against what the investment has delivered so far, and the return the business case committed to hasn’t shown up. The technology is doing its part, but the business isn’t changing around it.  

The gap sits with the workforce. Employees have been left to figure out AI on their own, unclear on what it means for their roles, how they are expected to use it, and where it fits into the work they are already accountable for. Some experiment on their own and find personal efficiencies. Others wait for direction that never quite arrives. And across the organization, adoption spreads unevenly, deep in some pockets and absent in others, none of it adding up to the enterprise capability the business case promised.  

The usual reading of that is resistance. In our experience, it is more often capacity and capability: the time to develop fluency with AI and the practice to apply it effectively, both constrained by the demands of the role. The fix is different, so the diagnosis matters. 

Closing that gap takes deliberate work across three layers: the leaders who set the direction, the managers who translate it into daily practice, and the employees who have to change how they work.  

This webinar walks through what that takes.  

You’ll leave with:  

• Why AI adoption stalls even when deployment succeeds, and the patterns that predict it 

• The three critical layers of AI adoption and how they reinforce each other in practice 

• What senior leaders, managers, and employees each need to do to move adoption from intention to reality 

• What the organizations getting this right are doing differently  

• How to measure whether the work is actually changing, and how to sustain the change over time 

For senior leaders accountable for the return on their organization's AI investment.