State of AI Search: B2B SaaS
The first comprehensive analysis of AI search visibility across B2B SaaS companies.
Overview
We tested 42 buyer-intent queries across ChatGPT (GPT-4o) and Perplexity (Sonar Pro) to see which of 100 B2B SaaS companies actually get recommended when prospects search for solutions. The results showed a clear divide: 47 companies were cited at least once, while 53 received zero citations across both engines. Among those cited, citation counts were low and tightly clustered — the highest total was just 3 citations, reflecting how thinly AI recommendations spread across a 100-company field.
Key Findings
53 of 100 B2B SaaS companies (53%) received zero citations across both engines
HR Tech was the most competitive sub-vertical — companies with strong G2 and analyst coverage appeared most often
22 companies appeared on both ChatGPT and Perplexity, while 25 appeared on only one engine
Perplexity cited more companies per query on average than ChatGPT
Among cited companies, those with Wikipedia pages, G2 profiles, and analyst coverage were overrepresented — though this correlation does not establish causation
Several well-funded SaaS companies with large marketing budgets received zero AI citations, suggesting traditional marketing spend alone does not guarantee AI visibility
Top 5 Companies by Total Citations
Per-Engine Breakdown
ChatGPT
GPT-4o
Perplexity
Sonar Pro
Methodology
Scope & Testing Window
100 companies in the B2B SaaS (HR Tech, Fintech, General) vertical were tested across 42 buyer-intent queries using 2 AI search engines: ChatGPT (GPT-4o, OpenAI) and Perplexity (Sonar Pro). Fieldwork dates: April 28 – May 12, 2026.
AI Engines & Configuration
ChatGPT was tested with web browsing disabled to isolate the model's trained knowledge from live search results. Perplexity was tested in its default mode, which retrieves and synthesizes live web sources.
Geography & Account Controls
All queries were run from US-based IP addresses using English-language prompts. Results may differ by region, language, and account history. Fresh browser sessions with no prior conversation history were used for each query batch. No custom instructions or plugins were enabled. ChatGPT was accessed via the Plus plan; Perplexity via the Pro plan.
Query Design
Queries were designed to represent buyer-intent searches — the kinds of queries prospects use when evaluating software or service providers. Informational queries (e.g., "what is endpoint security") were excluded. The full query set is available in the downloadable CSV.
Company Selection
100 B2B SaaS companies were selected based on three criteria: (1) active presence on G2 or Capterra with at least 10 reviews, (2) coverage across HR Tech, Fintech, and general SaaS sub-verticals, and (3) a mix of funding stages from seed to public. Companies were not selected based on existing AI visibility.
What Counts as a Citation
A citation is counted when a company is named as a recommendation, solution, or notable provider in an AI engine's response to a buyer-intent query. Passing mentions in disclaimers, generic lists of alternatives, or follow-up clarification prompts are excluded.
Scoring Rules
Each company received one citation point per appearance in an AI engine response, regardless of position within the response. A company mentioned first and a company mentioned last both receive one citation. No weighting by position, prominence, or sentiment was applied. Total citations = sum of appearances across all queries and both engines.
Repetitions & Statistical Note
Each query was run once per engine per testing session. AI responses are non-deterministic — running the same query again may produce different results. This study captures a single snapshot, not a statistical average. Because each query was run once (not repeated), these results represent a single observation per query-engine pair, not a statistical estimate. Confidence intervals and p-values do not apply. Treat the data as a structured snapshot of AI engine behavior during the testing window, not as a stable measurement.
Engine Coverage Note
This study covers two AI engines (ChatGPT and Perplexity). Google Gemini, Anthropic Claude, Microsoft Copilot, and other AI search products were not included. We plan to expand engine coverage in Q3 2026.
Research Lead
Andrew Swiler is the Founder of AnswerManiac and leads the company's primary research on AI search visibility. With a background in B2B marketing strategy and search optimization, he designed the State of AI Search methodology to give companies verifiable data on how AI engines represent their brands.
Sponsor Disclosure
This research was funded and conducted by AnswerManiac. No company featured in the study paid for inclusion or influenced its methodology or findings. AnswerManiac offers AI visibility optimization services, which creates a commercial interest in the topic studied. The raw data is published to allow independent verification.
Limitations
AI engine responses vary by session, account, and region. Results reflect a specific testing window.
Only two AI engines were tested. Google Gemini, Claude, and Copilot were not included. We plan to expand engine coverage in future quarters.
Citation counts reflect presence in responses, not position weighting or sentiment.
Queries were selected to represent buyer-intent searches; informational queries were excluded.
Each query was run once per engine. Results represent a single snapshot, not a statistical average across multiple runs.
Cite This Report
Andrew Swiler et al. "State of AI Search: B2B SaaS." AnswerManiac, May 15, 2026. https://www.answermaniac.ai/research/state-of-ai-search-b2b-saas
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Open Data
Full dataset available for download. Licensed under CC BY-NC 4.0.
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