Column: Steve Jobs may not have recalled the countless times he scraped his knees while learning to bike, yet he likened a personal computer to a ‘bicycle for the mind.’ The analogy highlights how tools can propel us further with minimal effort. Today, this statement reminds us of the learning curve inherent in adopting new technology. My initial encounter with the original Macintosh, touted as ‘intuitive,’ was perplexing without prior experience in its use. As with flying cars that exist more in imagination than practicality due to infrastructure limitations, AI requires knowledge and training to operate effectively. Just as it’s not feasible to master flying a car immediately, using AI without understanding its intricacies is equally challenging. Over the past few years, companies have distributed robust AI tools widely, often bypassing adequate training. This strategy underestimates the complexity of AI and overvalues users’ abilities. In skilled hands, AI can indeed simplify routine tasks, but it requires careful planning around workflow, processes, data, and expected outcomes. Neglecting these elements results in AI projects joining the many proofs of concept that never reach production. Nonetheless, businesses continue to hand over sophisticated AI capabilities to inexperienced users, anticipating rapid success and disappearing when issues arise. Anyone hoping for a shortcut to productivity with AI, without understanding the intricacies involved, is bound for disappointment. Buckle up!