Throughout 2025, I spoke with countless business leaders about their AI strategies, looking to glean insights into what was working for them and what was holding them back. As the year went on, I noticed three trends that kept emerging time and time again, across companies and industries, shaping which firms find success with AI and which struggle. Now I’m bringing these trends together, offering lessons from the front lines of AI transformation.
First, the use of AI for back-end tasks is booming, showing it’s often the boring stuff that can actually move the needle. The second trend isn’t about tech, but rather about people: How companies approach their people is paramount to how AI adoption unfolds. Perhaps the most telling trend, however, is all about initial strategy and motivation. Companies are failing when they lead with AI and finding success when they lead with the problem they’re trying to solve.
Of course, there’s so much more that goes into it—from wrangling data to security and governance. But these aspects of it are shaping AI efforts, for better or worse.
Avoiding AI for AI’s sake
Erik Brown, the AI and emerging tech lead at consulting firm West Monroe, told Fortune earlier this year that he’s seen a lot of companies struggle with “AI fatigue” after becoming frustrated with AI proofs of concept that failed to deliver. The common theme among those that fell into this position, he said, is that they explored the wrong use case or misunderstand how AI might (or might not) be relevant for the task. More specifically, they led with the idea that they wanted to pursue AI, rather than with the problem they wanted to solve.
