It seems like every product on the market is racing to add an “AI-powered” badge to its name. But as we move past the initial hype, a crucial strategic question is emerging for product leaders: are we building “AI-featured” products or “AI-first” products?
An “AI-featured” product bolts AI onto an existing workflow. Think of a smart grammar suggestion in a text editor or an AI-generated summary of a document. These are valuable, incremental improvements.
An “AI-first” product, however, is fundamentally built around an AI model as its core. The AI isn’t just a feature; it is the product. The entire user experience and value proposition would collapse without it. Think of products like Midjourney or ChatGPT itself.
This distinction is critical for roadmapping and long-term strategy. The former is about optimization, while the latter is about transformation. Building an AI-first product requires a different approach to user research, data strategy, and even how we define a “solved” user problem. It’s not just about sprinkling AI on top of our existing roadmap.
So, how is your team approaching this?