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Key Takeaways Many universities ban AI tools to protect academic integrity, but at work, they’re expected to leverage AI for speed, accuracy and innovation.
To close the AI-readiness gap, leaders should audit their hiring lens, partner with higher education, upskill internally and model curiosity.
As a Generation Xer, some would say we were 30 years old when we were 12, and today, in our 50s, we’re still 30 years old. We matured fast, but many of us remain young at heart. We snowboard, watch superhero movies and tinker with new technology, especially AI (as a leader, I’m obsessed with figuring out how to integrate AI into our business to bring more value to clients and improve bottom-line results). Many of us also now have kids who are between late high school and early career.
When speaking with this remarkable young generation, it’s clear they face challenges. At work, they’re expected to leverage AI for speed, accuracy and innovation. Yet in school, many are told not to use AI, or risk serious consequences. This disconnect leaves them trained for one reality while graduating into another.
If you’ve ever welcomed an impressive new hire who can code, research and present — yet freezes the moment you ask them to prompt an AI model or integrate its output into a project — you know this isn’t just a recruiting hiccup. It’s a collision between two worlds: the academy still navigating boundaries, and the workplace already operating at AI speed.
And when your next great hire arrives unprepared for how work actually works, that gap becomes your problem. This is no longer just an education policy debate. It’s a talent and leadership-readiness challenge every entrepreneur must navigate.
Related: 3 Ways to Prepare Your Business for an AI Future
Two worlds moving at different speeds
Companies are revamping entire workflows around speed, insight and automation. Technologies that took years to adopt now rise in months. Gallup reports that the use of AI at work has doubled in just two years, from 2023 to 2025. Leaders aren’t waiting. They’re investing in teams that can use AI to sift data, draft strategy, prototype ideas and scale execution. The statement that “one does not lose their job to AI, but to the person that knows AI” is now true more than ever.
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