You've invested in technology and introduced it to your people. How much has the work actually changed?
A request to use AI lands inside an existing organization. People already know which mistakes get noticed, how performance is judged, and whether there's time to learn. Asking them to experiment while leaving those conditions untouched can put competing demands on the same person.
Jordache draws on AI adoption experience and historical patterns to examine what leaders ask people to change, and what their organizations make possible. Resistance can reveal risks, threatened expertise, or working conditions that deserve attention. Technical and data constraints remain part of the picture.
The keynote gives leaders a way to examine their own part in adoption. It connects that responsibility to practical choices about expectations, learning, and how to judge whether a change is improving the work.
What your audience leaves with.
- 01
Why adoption stalls
How incentives, threatened expertise and old habits hold the work in place.
- 02
Activity or real change
How to tell usage numbers from work that actually got better.
- 03
Their part as leaders
One thing they control that makes trying new things safer.
- 04
One test worth running
A small adoption experiment, and the result that would justify keeping it.
Leadership groups, associations, and organizations whose technology investments have yet to produce the changes in work they hoped for.
“I’m incredibly grateful to Jordache for delivering such a powerful keynote at our event. His session on AI in the workplace was truly eye-opening and packed with practical, actionable insights. It wasn’t just informative. His energy was infectious, and his genuine personality made the content resonate even more. As someone who is always looking for ways to work smarter and more efficiently, I’m excited to start implementing some of the AI strategies and tools he shared into my own daily workflow. Thank you, Jordache, for inspiring our group and challenging us to think differently about how we adopt and scale AI within our organizations.”
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