AI UX Audit
AI UX Audit for Clearer, More Reliable User Journeys
I audit AI-assisted product flows to identify trust gaps, unclear interactions, human oversight needs, and conversion friction, then prioritize practical fixes your team can ship.
How I Help
- Map AI-assisted journeys: prompt entry, response review, correction loops, and task completion.
- Evaluate trust and transparency signals: confidence, limitations, fallback states, and error handling.
- Review human-in-the-loop controls, escalation paths, and places where legal or privacy review may be needed.
- Review interaction clarity across empty, loading, success, and failure states.
- Deliver a prioritized UX backlog tied to business and behavior outcomes.
Relevant Proof
Green Filter Decision Support
Research-led sustainability product work focused on helping users understand recommendations and act on decision-support cues.
- Connected user research to product framing and prioritization.
- Explored in-context guidance patterns for shopping and finance decisions.
- Translated behavior-change goals into clearer interaction patterns.
Related Work
Green Filter App
Research-driven sustainability product where decision support patterns had to be understandable and actionable.
Green Filter Chrome Extension
In-flow guidance prototype tested in live browsing contexts to validate behavior-change interaction quality.
WiFi.ee
Cross-platform journey design work balancing UX clarity, technical constraints, and real purchase behavior.
FAQ
What is included in an AI UX audit?
I review user journeys, response trust signals, state behavior, and decision clarity, then provide prioritized fixes with implementation guidance.
Do you work with existing products or only new builds?
Both. I can audit an existing AI feature or support AI UX decisions from prototype through production.
How quickly can we act on findings?
The output is built for execution: concrete friction points, expected impact, and a practical implementation sequence.