The article explores how using AI can lead to increased workloads instead of relieving them, tying this phenomenon to Parkinson’s Law, which states that work expands to fill the time available. The author reflects on their own experience with AI, where improved efficiency quickly leads to an expanded to-do list. Instead of enjoying the time saved, many people fill it with new tasks, perpetuating a cycle of busyness. This challenges the notion that AI will create a utopia with fewer jobs; instead, it suggests that people will often take on more work. The piece highlights the risks companies face when cutting jobs in favor of AI. Many workers hold essential knowledge that is not well documented, making it difficult for AI systems to operate effectively. This lack of documentation can create more problems than it solves, requiring additional human effort to retrain systems later. The author argues that rather than downsizing, companies should consider hiring more people to leverage the productivity gains AI offers. A growth mindset sees AI as a tool to tackle previously insurmountable challenges, rather than a reason to eliminate jobs. The article also touches on the broader implications of AI use, emphasizing that there are plenty of problems to solve in the workforce and beyond. It suggests that a fixed mindset may lead executives to make shortsighted decisions about workforce reductions, whereas a growth mindset can open up new avenues for innovation and productivity. The author ultimately finds themselves caught in a cycle of work driven by AI, reflecting a common experience in today’s work culture.