Microsoft has added a beta Topics Portfolio view to the AI Performance report in Bing Webmaster Tools. Instead of forcing SEO teams to inspect AI-search visibility query by query, the report groups grounding queries into broader topic clusters and adds directional measures such as topic size, sites cited, query count and opportunity queries.
That is a meaningful shift for content teams. AI-search reporting is still early, incomplete and uneven across platforms, but topic-level evidence is more useful for planning than a pile of isolated queries. It helps teams ask: where are we already being cited, where is demand large enough to matter, where is competition crowded, and which gaps are worth assigning to editorial or product experts?
Do not read it like Search Console
Microsoft is careful about the beta caveats. Topic classification is AI-generated and may be imperfect. Smaller sites may not see enough data. Branded queries can appear as opportunities. Topic size and citation volumes are approximate. That means the report should not be used as a precise ledger of traffic or revenue.
The better use is diagnostic. Treat each topic as a planning zone. A topic with meaningful current citations may need authority maintenance, source updates and internal links. A large topic with many cited competitors but few citations for your site may deserve a gap review. A small topic with strategic importance may still be worth improving if it sits close to a product or service decision.
A practical audit process
1. Sort topics by business relevance first. Do not chase the biggest topic automatically. Mark which clusters connect to commercial pages, category expertise, support costs, local demand or executive priorities.
2. Compare presence and competition. Topic size tells you whether AI-search demand exists. Sites cited tells you whether the topic is crowded. Your own citations show whether Bing already sees you as useful. The combination is more important than any one number.
3. Open opportunity queries with skepticism. Some will be too broad, branded for competitors or misclassified. Keep the queries that reveal a missing answer, weak evidence page, outdated guide or unclear product explanation.
4. Assign the right fix. Not every gap needs a new article. Some need better source references, updated statistics, clearer author credentials, comparison tables, FAQ sections, stronger internal links or product-page copy that answers the query directly.
5. Review monthly, not daily. AI-search visibility changes with content, citations and the wider web. A monthly topic review is enough for most teams and avoids overreacting to approximate beta signals.
The takeaway
The value of Topics Portfolio is not that it finally makes AI search fully measurable. It does not. The value is that it gives SEO and content teams a shared map for prioritization. When traffic is fragmented and attribution is thin, a directional map is still useful if it leads to better decisions: fewer generic posts, more evidence on important topics and clearer ownership of gaps that actually affect the business.
Source references
- Microsoft Bing Blog: Introducing Topics Portfolio (Beta) in AI Performance
- Search Engine Land: Bing Webmaster Tools AI performance report new Topics Portfolio
