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AI trust is breaking products

When users stop trusting AI, adoption drops, decisions stall, and teams lose confidence in their own systems.

I help teams design AI experiences users actually trust.

Request an AI UX trust audit

Why AI products fail in practice

AI products rarely fail because the technology doesn't work.

They fail because users can't tell when to trust them.

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What's going wrong

Confidence without Context

Hidden uncertainty

Disclaimer Instead of Design

Trust Treated as Copy

Users double-check, ignore, or abandon features silently.

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My area of focus

  • AI decision-making

  • Human-Centered UX

  • Enterprise Product Reality

I evaluate trust across

  • Inputs & outputs

  • Error Handling

  • Human-in-the-loop

  • Product Risk

What you get

  • UX Trust Scorecard

    • An assessment across key trust dimensions, highlighting strengths, risks, and gaps.

  • Annotated UX Findings

    • Concrete examples showing where AI outputs, uncertainty, or errors create confusion or misuse.

  • Risk & Opportunity Summary

    • A concise view of how trust issues translate into adoption, decision quality, and business risk.

  • Prioritized Recommendations

    • Actionable guidance focused on high-impact improvements—not redesigns for redesign’s sake.

  • Executive-Ready Readout

    • A structured summary designed to align product, design, and leadership on next steps.

“I help product teams design AI experiences that users can actually trust, before trust issues turn into churn, risk, or internal fire drills.”
Let's talk!

*Disclaimer: Content was generated by MLL; human-validated, and updated accordingly. 

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