It feels like every product strategy discussion in the last six months has been dominated by one acronym: AI. Executives are asking for an AI strategy, VCs are funding it, and marketing wants to slap an ‘AI-powered’ sticker on everything. But in this rush, are we losing the plot?
I’m seeing a worrying trend of ‘AI feature-stuffing’ — shoehorning generative AI into products without a clear user problem to solve. It’s the 2020s version of ‘let’s put it on the blockchain.’ We get so mesmerized by the tech’s capability that we forget to ask the most fundamental product management question: ‘What user problem are we solving, and is this the best way to solve it?’
Building a half-baked AI feature that doesn’t truly address a user need is more than just a waste of engineering cycles. It adds complexity, confuses users, and bloats the product. It’s a distraction from the core value proposition. True innovation happens when we apply new technology to solve old, painful problems in a novel way, not when we treat the technology itself as the end goal.
So, how are you and your teams navigating this pressure? How do you separate the genuine, user-centric AI opportunities from the pressure to just ‘add some AI’ to the roadmap?