Why Eliminating Jobs Because of AI is Failing and How to Get It Right

Companies like Klarna made headlines for replacing 700 customer service workers with AI agents, only to quietly hire them all back 18 months later. IBM laid off 8,000 employees to implement AI systems, then had to bring people back when they realized the 15% of problems AI couldn't handle contained all the real risk. This episode reveals why the "AI will eliminate jobs" narrative is backfiring spectacularly. Join Michael LaVista, CEO of Caxy Interactive, and COO Hannah Deason as they break down what's really happening with AI in the workforce. You'll discover Hannah's "TJR Scan" framework (Time, Judgment, Risk) for identifying what should actually be automated, learn about the "Decent Effect" - why removing all easy tasks makes jobs unbearably difficult, and understand why companies that think they can eliminate entire roles might have contempt for their own workforce. Hannah Deason is COO at Caxy Interactive, where she's been implementing AI solutions for 5+ years. She specializes in AI integration that enhances rather than replaces human capabilities, and has developed frameworks for successful AI adoption that preserve workforce development pipelines. If this episode changed how you think about AI and jobs, hit subscribe for more insights on digital transformation that actually works. Drop a comment with your own AI implementation experiences - we'd love to hear what's working (and what isn't) in your industry. Like this episode if you think more leaders need to hear this message before they make expensive mistakes with their workforce. Get Mike's book "Superpowered" on Amazon: https://www.amazon.com/Superpowered-Leadership-Superpowers-Tech-driven-Organization-ebook/dp/B09D9XWWZS Caxy Interactive -- Showing organizations how to play offense with software and AI.https://www.caxy.com | [email protected]