AI features only pay off when people can find them, understand them, and trust them enough to act. Plenty never get there: the model works, but the experience around it leaves users unsure what happened, why, or what to do next.

At Coupa I led UX for Spend Guard, an AI anomaly detection product for enterprise finance teams. Reworking how its insights were surfaced and explained contributed to 106% year-over-year growth in adoption. This review applies the same lens to your product.

Discoverability: can people find the feature when it would help them?

Explainability: do users understand what the AI did and why?

Confidence signals: does the interface show how sure the system is?

Failure modes: what happens when the AI is wrong, and can users recover?

Control: can users review, override, and correct the output?

Workflow fit: does the feature help the surrounding task or interrupt it?

A prioritized findings report: what's broken, why it matters, and what to change, ranked by impact and effort

Annotated screens showing each issue in context

Quick wins your team can ship right away, plus recommended patterns for the bigger fixes

A 60-minute walkthrough with your product and engineering leads

Scope is one AI feature or core workflow, delivered in five business days. Larger scopes quoted separately. Not building AI? The same review works for any complex B2B workflow: onboarding, approvals, and data-heavy dashboards.