We Asked 3 AI Engines to Recommend Field-Service Software. They Disagreed on Almost Everything.
First-party audit: we ran 8 buyer prompts through ChatGPT, Perplexity, and Gemini. Two companies owned the category. The rest were invisible where it counts. The mid slots changed on every engine.
We asked ChatGPT, Perplexity, and Gemini to recommend field-service software across 8 buyer questions. Two companies dominated every niche. The rest were invisible where it counts, or only showed up on one engine. The top 3 picks agreed across engines. After that, the answers diverged almost completely. The same company can be recommended by one engine and missing from the other two.
If you sell field-service software and your buyers ask AI for recommendations, this is the data that shows whether you exist in those answers. We ran real buyer prompts across three major AI engines, recorded every brand they cited, and mapped who owns the category, who is invisible, and where the engines disagree. This is JYNLAB's first-party audit data, not a survey or a vendor report.
How we ran this audit
We ran 8 buyer-intent prompts through Perplexity (logged in, web search), then cross-checked two prompts on ChatGPT (with web search) and Gemini (with grounding). Each prompt follows the pattern a real buyer would type: "best field service software for [trade/use case]".
We recorded every brand named in the answer, in order. No sponsored placements, no paid inclusion. These are the brands each engine chose to cite on its own. The audit was run in June 2026.
Share of model: who AI actually recommends
"Share of model" is how many of the 8 buyer niches an engine cites you in. The higher the number, the more buyer questions you show up for. Think of it as market share inside AI answers.
| Company | Niches cited (of 8) | Engines (of 3) | Tier |
|---|---|---|---|
| Jobber | 6 | 3 | leader |
| Housecall Pro | 6 | 3 | leader |
| ServiceTitan | 4 | 2 | mid |
| FieldEdge | 3 | 1 | mid |
| FieldPulse | 1 | 2 | weak |
| Workiz | 1 | 1 | weak |
| Service Fusion | 1 | 1 | weak |
Jobber and Housecall Pro own the category. They appear in 6 of 8 niches and on all three engines. If a buyer asks any AI engine for field-service software, these two are almost always in the answer. Everyone else is fighting for the remaining slots, and most are losing.
What each engine recommends, niche by niche
The generic "best field service software" prompt and the trade-specific prompts return different companies. A brand that shows up in the generic answer can be completely absent in pest control, HVAC, or cleaning. The niche is where the real buyer intent lives.
| Buyer question | Cited (Perplexity, in order) |
|---|---|
| Small business (general) | Jobber, Housecall Pro, FieldPulse, Service Fusion, Workiz |
| Pest control | FieldRoutes, GorillaDesk, PestPac, ServiceTitan, Housecall Pro |
| Residential cleaning | Jobber, ZenMaid, Housecall Pro, Swept |
| Appliance repair | Housecall Pro, ServiceTitan, Fieldproxy, FieldEdge, SamPRO |
| HVAC contractors | ServiceTitan, Housecall Pro, Jobber, FieldEdge |
| Plumbing companies | Jobber, Fieldproxy, FieldPulse |
| Electrical contractors | ServiceTitan, Jobber, Housecall Pro, FieldEdge, Procore |
| Lawn care / landscaping | Jobber, LawnPro, Connecteam, Crew Control, Zoho FSM |
The engines disagree: same question, different answers
This is the strongest finding. We asked all three engines the same question: "best field service software for pest control". The top 3 picks were the same. After that, each engine recommended a different company that the other two did not mention at all.
| Engine | Recommended (in order) | Unique pick |
|---|---|---|
| Perplexity | FieldRoutes, GorillaDesk, PestPac, ServiceTitan, Housecall Pro | ServiceTitan |
| ChatGPT | FieldRoutes, PestPac, GorillaDesk, Briostack, Jobber | Briostack |
| Gemini | FieldRoutes, PestPac, GorillaDesk, QuoteIQ, Jobber | QuoteIQ |
ServiceTitan only shows up on Perplexity. Briostack only on ChatGPT. QuoteIQ only on Gemini. If you only check one engine, you are seeing a third of the picture. This is why AEO has to be tracked per engine, per prompt, on a regular cadence.
Who is invisible where it counts
The companies with the biggest gap between where they show up and where they are missing:
- FieldPulse and Workiz appear in the generic "small business" prompt but vanish in every trade-specific niche (pest, cleaning, HVAC, appliance, lawn). They are in the waiting room but not in the exam room. The trade-specific prompts are where buying intent is highest.
- ZenMaid, LawnPro, GorillaDesk own exactly one niche and are invisible in everything else. Growth means expanding into adjacent trade queries, not just defending the one they have.
- Service Fusion appears in the generic prompt only. Zero niche presence despite being a full-featured FSM platform.
What this means for your AI visibility
- Category leaders are decided. Jobber and Housecall Pro are the default AI answer. Displacing them is hard. But the 3rd-5th slots are wide open and change by engine.
- Niche wins are easier than category wins. Owning "best FSM for pest control" is far more achievable than "best FSM for small business", and the niche query is where the buyer is actually deciding.
- You cannot eyeball this. Checking ChatGPT once is not an audit. The engines disagree on the mid-to-tail picks, and those are the positions you are competing for.
- Generic visibility is a trap. Showing up in "best FSM for small business" but not in any trade niche means you are visible to browsers, not buyers. The conversion happens in the niche prompt.
FAQ
How do AI engines decide which field-service software to recommend?
They retrieve candidate sources for the query, weight them by authority, third-party consensus (reviews, comparisons, community mentions), relevance to the specific trade, and freshness. The clearest, most corroborated answer wins the citation. There is no paid placement.
Why do ChatGPT, Perplexity, and Gemini recommend different companies?
Each engine uses different retrieval sources, different weighting, and different training data. In our audit, the top 3 picks for pest control were the same across all three engines, but the 4th and 5th picks were completely different. The mid slots are engine-specific.
My company shows up in the generic prompt but not in trade-specific prompts. Is that a problem?
Yes. The generic prompt ("best FSM for small business") attracts browsers. The trade-specific prompt ("best FSM for pest control") is where the buyer is actually deciding. If you are invisible in the trade prompt, you are missing the highest-intent buyers.
How often should I check my AI visibility?
At minimum monthly, across at least three engines. AI answers change as new content is indexed and retrieval sources shift. A single check on one engine gives you roughly a third of the picture.
Can I pay to show up in AI answers?
No. Major AI answer engines do not sell placement in their recommendations. Visibility is earned through content clarity, structured data, and third-party consensus, not ad spend.
See where your business stands
We run your brand through ChatGPT, Perplexity, and Gemini and show you exactly what comes back, who gets cited instead, and where the gap is. Free, no pitch unless you ask.
Five years across software engineering, product management, and AI building. She built two AI products from zero to one, reverse-engineered how answer engines select and cite sources, and now runs JYNLAB, a done-for-you AEO agency for B2B. Work with Jenny →