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AI user experience

As explained in The Art of AI Product Development

AI user experience is the quality and character of interactions with a product whose behavior or outputs depend on artificial intelligence.

In a sustainability reporting app, an AI-assisted editor might let someone work through chat, voice, or inline actions. The design challenge is not just choosing controls: users may have different intentions, and the AI may behave in ways that become clear only after launch. section 10.2.2

Practical AI UX patterns help people understand and steer the experience:

  • Explain predictive scores and values with interactive tooltips. section 10.2.2
  • Offer prompt suggestions or simple controls for calibrating output style. section 10.2.2
  • Encourage verification, show original sources where useful, and let users stop a generation that has gone off track. section 10.2.2

Aim for calibrated trust rather than assuming every answer deserves confidence. Start with a small area of personalization, then collect feedback on both the interface and AI performance once an MVP is live; expect to revise both. section 10.2.2

How The Art of AI Product Development covers it

How deep it goes
Offers design patterns and iteration advice, but defers fuller pattern guidance to external resources.
Examples
Uses an adaptive sustainability-reporting editor and examples of tooltips, prompt suggestions, style controls, and generation stopping.
What you can do after
Practice/perform iterative AI interface design by starting small, collecting live feedback, and adjusting both UI and AI performance.
How it connects
Connects personalization, conversational interfaces, data visualization, predictive AI, and calibrated trust.

This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.