When a Fortune 500 financial services company approached Bitovi to modernize its design system, the team was drowning in prototype complexity. Designers were spending 50% of their time building prototypes for every interaction, state change, and validation message. The culprit? A design tool that forced everything to be a functioning prototype.

Google’s newest AI tool, Stitch, promises to speed up the product design process. But does it actually accelerate design, or does it create “design debt” that organizations must reckon with later in their product lifecycle?

AI can be transformative, but it can also fail spectacularly if user experience and real-world needs aren’t top priorities. Sometimes, the biggest danger is what you don’t see: overconfidence in AI’s novelty, untested assumptions, and a fuzzy plan for how users will adapt. Below, we’ll explore the six biggest ways AI projects go off the rails, along with strategies to mitigate risk and apply a rigorous process to your next AI initiative.

In fast-paced development timelines, teams are often forced to skip critical steps in the design process. Unfortunately, user testing is one of the most commonly omitted steps. In an effort to save time in the short term, significant usability issues often arise, requiring more time to correct them in the long run.

Product design projects involve many moving parts. Between design requirements, roadmaps, research findings, and documentation, information can become scattered. Without a central source of truth, teams can waste valuable time tracking down the latest updates.