Designing Control: Integrating AI Summaries into a B2B Knowledge Platform

AI · 6 min read

The product team at a B2B knowledge platform wanted to reduce time-to-insight for support and sales teams by introducing automatic document summaries. Designers prioritized an architecture where AI is an assistant, not an authoritative source: every summary is shown as "AI-generated" with a clear confidence badge and a one-click path to view the source passages used by the model.

To combat hallucination, the interface exposes provenance—highlighting the original sentences used and enabling users to flag inaccuracies with a single click. Early user testing with 50 pilot users found that when provenance was visible, trust scores rose 38% and edit rates doubled, meaning users corrected summaries more often than they ignored them. Designers used an edit-first workflow: edits are treated as signals to the system, improving future summaries through supervised fine-tuning pipelines.

The rollout included two UX patterns: inline editable summaries for quick corrections, and a "suggested summary" mode where AI provides bullets that the user can accept or reject individually. The team's lesson was practical: give users control, make the AI's work transparent, and capture edits as product signals — this reduces fear and increases adoption in enterprise environments.