2,831 buyer questions no brand owns yet: AI recommendation white space by industry

Of the 7,248 buyer questions Parse tracked, 2,831 (39%) had no consistent leading brand. The rate ranged from 26.2% in Gaming to 51.2% in Sports. These open questions are useful targets because no competitor has established a durable lead. Brands should prioritize open questions that match their product and have enough observations to measure.

Four in ten buyer questions have no brand on top

Parse groups prompts into recommendation contexts: distinct buyer jobs inside a category, such as "short-term emergency cash" or "cloud cost optimization." We track 7,248 monitored buyer questions. Of those, 4,417 (61%) are owned, meaning one brand is the consistent leading answer. The other 2,831 (39%) are open: AI names brands, but none leads consistently. Every open question has brand evidence behind it, so these are active questions rather than empty records.

How we measured it

Parse resolves the prompts AI answers into recommendation contexts, the distinct buyer questions within each category, and tracks which brand, if any, AI consistently recommends for each. A question is owned once a single brand emerges as the leading answer; it stays open when AI names brands but none has pulled ahead enough to lead. We counted 7,248 real buyer questions across categories, excluding contexts that were noise or duplicates of another question. Of those, 4,417 are owned and 2,831 are open. We verified that open questions are real demand, not empty records: every one has brand evidence behind it, drawn from AI's own answers. They average 2.4 distinct named brands, and the most contested reach into the twenties. The split is a structural snapshot of where AI has and has not committed, scoped to Parse's monitored prompt panel and reported in aggregate.

Owned and open questions need different plans

In an owned question, the leading brand holds an average 38% of AI's recommendation weight, with a 29% median. Displacing that default requires evidence across many answers and usually takes time. In an open question, AI already names candidates but has no consistent leader. Most open questions average 2.4 named brands, and 506 have had only one brand mentioned. More crowded open questions also exist: 228 have five or more named brands and 77 have ten or more. Teams should favor relevant open questions with limited competition and sufficient repeat observations. As Parse's analysis of crowded buyer questions shows, being named does not mean a brand owns the answer.

The white-space rate swings from 26% to 51% by industry

The open rate varies by more than two to one across well-tracked categories. Mature, consolidated categories such as Gaming and Data and Analytics have a consistent leader for most questions. Sports, Health Care, and Real Estate have more questions without one. The table below shows industries with enough tracked questions for comparison.

Smaller categories have higher rates, including Agriculture and Farming at 62.8% and Events at 60.9%, though both have fewer tracked questions. The exact rank is less useful than the range. In some categories most questions have a leader; in others nearly half do not. The category rate helps determine how much work should protect existing positions versus pursue open questions.

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Where the most open questions are

A high open rate in a small category is fewer real opportunities than a moderate rate in a large one. By raw count, the biggest pools of open questions sit in Parse's largest tracked categories: Financial Services has 310 open buyer questions, Software 242, Information Technology 227, Commerce and Shopping 160, and Artificial Intelligence 136. These are the categories where AI fields the widest range of buyer jobs, so even a sub-average open rate leaves hundreds of unclaimed recommendations. The practical read: if you sell into one of these large categories, the volume of open questions is large enough that you do not need to displace an incumbent to win AI visibility. You need to find the specific buyer jobs in your category that AI is already fielding without a default answer, and become that answer before a competitor does.

What an open buyer question looks like

Open questions are concrete buyer jobs, not abstractions. The ones below are among the most contested, where AI named between 19 and 29 brands across its answers and settled on none. Each is a real recommendation AI is handing out inconsistently right now.

These are the loud end. The typical open question is quieter, averaging just 2.4 named brands, which often makes it easier to claim, not harder. Either way the pattern is the same: AI is fielding the demand and has not decided, so the answer is still available to whichever brand earns it first.

What this means for your AI visibility plan

Sort the category's buyer questions into owned and open groups. For owned questions where a competitor leads, select the few that justify sustained evidence work. For open questions, prioritize those with clear buyer intent, few named competitors, and enough observations to confirm the result. Then publish or earn the specific evidence those answers already cite. Recheck the same prompts on a fixed schedule because an open question can gain a consistent leader.

How Parse maps this for your category

Parse tracks AI visibility across ChatGPT and Google's AI search surfaces, covering a public index of more than 4.7 million AI responses, 603,000 brands, and 57 million citations. The 39% open rate is the cross-category average, not your number. A consolidated category like Gaming leaves far less open than a fragmented one like Sports or Health Care, and within any category the specific open questions are what you act on. Parse's Rankings view breaks your category into the buyer questions AI actually fields, shows which brand leads each one and which have no owner, and surfaces where competitors are pulling ahead on a question you could still claim. For the adjacent question of where AI cites competitors and not you, see our AI citation gap analysis framework, and for the mechanics of how AI settles on a brand in the first place, how ChatGPT decides which brands to recommend. Find the open buyer questions in your category.