“They want their brand to be seen as AI-first but often apply it to non-urgent problems — like experimenting with content generation, for example, instead of identifying a core business issue to fix,” he says. “It’s not about simply jumping on the AI train. It’s about being sure that you’re riding it in the right direction and that you even need it in the first place.”
Not enough expertise
Many IT and business leaders have rushed into AI adoption without considering internal expertise or the need to sell the technology to internal users, prompted in part by a fear of missing out, Navodnyy contends.
“When leaders feel the pressure to move fast just to stay competitive, they can sometimes skip critical steps, prioritizing deployment speed over product quality,” he explains. “That’s a very reckless approach, and an easy way to end up with wasted resources and damaged reputation.”
