What AI search recommended this week
28 September 2026 · Based on 120 recorded test runs · AI Visibility Index
AI search engines do recommend local businesses, but the pattern is not fixed: the names change by city and by wording, and the same service can surface different leaders when the prompt changes slightly. In the recorded tests for house cleaners, Denver showed the strongest concentration around a single business, while Austin and Chicago were more split across several names.
What the data shows
For house cleaner in Austin, TX, the top name in 20 test runs was Eleven Friends of Grumpy Brush, which appeared in 95% of answers. Sparkly Maid Austin Cleaning Services followed at 90%, then Tidy Hands Cleaners at 65%, Maids and Moore at 55%, and DF CLEANING LLC at 25%.
When the query changed to house cleaner in Austin, TX?, the mix shifted. Sparkly Maid Austin Cleaning Services led at 85%, while MoreHands Maid Service and Tidy Hands Cleaners were each named in 75% of answers. Eleven Friends of Grumpy Brush fell to 65%, and Maids and Moore to 40%.
For house cleaner in Chicago, IL, the most named business across 20 runs was The Deep Cleaners at 85%. The next group was much lower: House Keep Up at 45%, Homeaglow at 35%, Sparkly Maid Chicago at 30%, and Sparkly Maid at 30%.
The Chicago variation with a question mark again changed the ordering. The Deep Cleaners still led, but dropped to 55%. Molly Maid rose to 45%, Sweep Home Chicago reached 40%, King of Maids also reached 40%, and Happy Home Cleaning Chicago appeared in 35% of answers.
Denver was the most decisive market in this set. For house cleaner in Denver, CO, Alpine Maids appeared in 100% of answers across 20 runs. MaidPro Denver followed at 80%, Merit Maids at 65%, and both Superb Maids Denver and The Maids at 50%.
The Denver question-mark variant was still highly concentrated, but the lead changed. MaidPro Denver was named in 95% of answers, Alpine Maids in 80%, The Maids in 75%, Merit Maids in 70%, and Kathy Clean in 35%.
Taken together, the tests show that AI search engines are not returning one universal local ranking. They are surfacing a small set of recurring businesses, but the order can shift with tiny prompt changes, and the lead business can change even when the query is nearly identical.
What this means if you’re a local business
The practical lesson is that AI visibility is now a citation-and-entity problem, not just a traditional search ranking problem. If a business wants to be named consistently, it needs clean crawler access, strong entity signals across the web, and citable answers on its own site and in third-party listings.
That means the business name, address, phone number, service area, and category language should match everywhere the model is likely to check. It also means the website should plainly describe what the company does, where it operates, and what makes it a relevant answer for the query. Reviews, directory profiles, and local mentions matter because AI systems often assemble recommendations from multiple sources rather than from one authoritative list.
The data here also suggests a simple testing habit: ask the same service query in more than one form. A small punctuation change was enough to alter which businesses appeared most often in Austin, Chicago, and Denver. If the prompt changes the answer, the business is not yet fully stable in AI search.
FAQ
Are these the only businesses AI search engines recommend?
No. These tests show the most frequently named businesses in a limited set of prompts and 20 runs per prompt. Other businesses may appear in other queries, locations, or AI systems.
Does a higher percentage mean the business is always first?
No. It means the business was named in that share of answers, not that it was always placed first or framed the same way. The key pattern is consistency across repeated tests.
All numbers above come from recorded test runs published in our open data index. Want your business tested? One-time diagnostic, no subscription.
Originally published at the AI Visibility Index.
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