Shadow AI? Non, Merci. A Secure AI Adoption Dinner and Discussion

Your employees are already using AI. The question is whether they are using it safely.
Shadow AI is not a problem you can block your way out of. Sanctioned tools sit unused while sensitive data flows into whatever app is easiest for employees to use. Acceptable use policies exist, but few employees could tell you what theirs actually says. The security teams getting this right are not the ones with the strictest controls. They are the ones changing how their people work with AI every day.
Join Myriad360, Fable Security, and Victor Bennett, Professor of Entrepreneurship and Strategy at the University of Utah, for an intimate dinner at Black Hat USA, overlooking the Strip. Victor will lead a candid conversation among a small group of security leaders on what is actually working:
Helping employees understand their AI acceptable use policies in plain language they will remember
Rolling out sanctioned tools so the safe path is also the easy path
Helping employees recognize the risk in unsanctioned AI before they paste in the wrong thing
Catching and correcting shadow AI use without slowing the business down
Victor brings a rare vantage point on how technology reshapes the way companies work. His research on how technology affects entrepreneurial ventures and established companies' ability to sustain performance has appeared in journals like Management Science and the Strategic Management Journal, and he previously served as Senior Economist for Technology and Competition Policy at the White House Council of Economic Advisers.
We will share what we are learning from customers who have driven secure AI adoption across their orgs, and with Victor guiding the discussion, you will leave with approaches you can put to work the moment you are back at your desk.
The details
Tuesday, August 4 at 6:00 PM, a short ride up the Strip from Mandalay Bay
Complimentary Uber rides to and from the restaurant
Seats are limited and the table fills quickly. Reserve yours below.