Many companies silently assume that everybody wants more AI in their lives. That people are craving new AI features, new AI products, new AI workflows — that would all magically replace all existing outdated practices and broken ways of working.

But in reality, it seems like people don’t want more AI at all — at least not in the way most AI leaders envision it. Unsurprisingly, many AI features have low adoption and retention — at a very high cost of delivery, and a high risk of reputation damage.

The AI People Don’t Need

It’s remarkably difficult to make a strong argument with senior leadership, but AI is not a value proposition. New AI features don’t magically make for happy or excited customers. Because AI features are often bolt-ons and separate tools for employees to use, they typically take people out of their regular way of working.

AI is pretty good at amplifying shortcuts and shortcomings in organizations — from data quality to decision making. It can’t magically fix years of accumulated quick patches, technical debt, broken culture and internal politics. If anything, they become more visible with AI as inconsistencies or conflicting priorities and get handed directly to users, who are then left to make sense of the mess themselves.

Because in most organizations, work typically requires hopping on and off between plenty of disconnected and fragmented systems, with a new AI tool, they now have yet another system that they also need to hop on and off. Often it produces more work, and typically it’s not particularly rewarding work either.

On top of that, people are very much aware of the cost of finding and fixing AI hallucinations. Asking AI to generate a response might feel easier than writing from scratch, but it has a cost:

  • Skim through the entire AI output,
  • Spot key points to focus attention on,
  • Review/verify key points, one-by-one,
  • Check rationale for what follows next,
  • Articulate corrections + regenerate,
  • Review the response…

    Source: Smashing Magazine (Published: Wed, 15 Jul 2026 10:00:00 GMT). Read the full article on the original site.