Many companies assume everyone craves new AI features. But the reality is that most people don't want more AI — at least not in the way most AI leaders envision it. Brought to you by Design Patterns For AI Interfaces, **friendly video courses on UX** and design patterns by Vitaly.

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Smashing Magazine

Most companies assume users crave AI features, but data shows low adoption and retention. People resist AI that disrupts existing workflows, introduces unpredictability, or amplifies organizational dysfunction. What people actually want is AI that quietly automates tedious, repetitive tasks while staying deeply integrated into existing mental models — not AI-first products, but 'AI-second' tools that are subtle, reliable, and augment rather than replace human work. The piece argues that speed of delivery is not the value most users seek; they want reliability, predictability, and the ability to enjoy meaningful work.

No, People Don’t Want More AI In Their Life — Smashing Magazine

Meet “Design Patterns For AI Interfaces”

<p>“AI-second” is the right frame, and the engineering reason underneath it is trust calibration. An assistant that’s brilliant 85% of the time but fails unpredictably is often worse than none, because the user now has to verify every output — you’ve added a review step, not removed work. Reliability, not capability, is the adoption gate.</p>
<p>That’s why the quiet, scoped automations win: when a feature does one narrow thing predictably, people learn where to trust it and stop checking. Open-ended “AI-first” assistants never earn that, because their failure surface is unbounded — you can’t build a stable mental model of something that might do anything. The teams getting real adoption aren’t shipping smarter models, they’re shipping smaller, more predictable promises.</p>
