How do you handle search results that reference old legal issues that have been resolved?

Resolved legal issues that continue to appear in search results are one of the most common situations clients bring to reputation programs. The response runs through a sequence of interconnected layers, each reinforcing the others as the engines re-index the current picture.

Step 1: Build authoritative owned content covering the resolution

Publish a dedicated page on the corporate site or news hub that covers what was alleged, what was resolved, and what the current status is. The page should carry proper structured data and schema markup so the engines can extract the content cleanly. This creates the canonical authoritative reference the other layers can point to.

Step 2: Request updates from outlets that covered the original matter

Many credible outlets accept update requests for clearly resolved matters when the request is accompanied by documentation (settlement agreements, court dismissals, official announcements). Submit update requests with the relevant sourcing. Not every outlet will comply, but many do for factually closed matters.

Step 3: Update Wikipedia through the Talk-page edit-request process

Wikipedia articles frequently remain frozen at the dispute or accusation phase after a matter closes. Propose changes through a disclosed Talk-page edit request, backed by reliable secondary sourcing for the resolution. An independent community editor reviews the request and, if the sourcing supports it, implements the change. The goal is to ensure the article reflects the closure proportionally rather than leaving it frozen mid-dispute.

Step 4: Refresh the Knowledge Panel

Where the entity has a Google Knowledge Panel, use the verified entity correction process to suggest updated information reflecting the current state. The panel’s substantive content draws from underlying sources, primarily Wikipedia and Wikidata, so panel updates follow source corrections rather than precede them.

Step 5: Monitor AI engine treatment with AIQ

AI engines often continue describing closed legal matters as live after resolution, because their training data and retrieval sources include legacy coverage that preceded the closure. Run AIQ monitoring across the major AI engines to track how they are describing the matter and identify which sources are driving their responses. Persistent updating across sources is required to shift the AI narrative.

Timeline expectations

• Weeks 1, 4: Owned resolution page published and indexed; outlet update requests submitted.
• Months 1, 2: Wikipedia Talk-page edit request filed and, where accepted, implemented; Knowledge Panel correction submitted.
• Months 2, 6: AIQ monitoring tracks AI engine narrative; authoritative resolution content accumulates across sources.
• Months 3, 9+: The SERP picture rebalances as engines re-rank around the weight of resolution content versus legacy coverage. AI engines are typically the slowest layer to update.