Software is the category where AI chatbots have moved fastest from a curiosity to the default research tool, and the data on what that is doing to vendor selection is now specific enough to act on. G2's own 2026 AI Search Insight Report, based on a March 2026 survey of 1,076 B2B software buyers and decision-makers across North America, EMEA and APAC, found that 51% now start their software research with an AI chatbot more often than with Google, up from 36% seven months earlier. More strikingly, 69% of those buyers ended up choosing a different vendor than the one they originally expected, and 33% bought from a brand they had never heard of before the AI conversation started. For a SaaS company, that means the shortlist is increasingly being built by a chatbot before a salesperson ever gets a call.
Source: G2's 2026 AI Search Insight Report, a March 2026 survey of 1,076 B2B software buyers, linked in the article.
How fast is this actually moving?
Fast enough that G2, which has an obvious commercial interest in the answer, is still worth reading carefully because its own citation data backs up the buyer-survey numbers. Separately from the buyer survey, G2 reports being cited across more than 115 million software category searches in AI systems, averaging 1.53 million daily AI citations as of mid-2026, a figure it says nearly tripled since March 2026. That is G2 describing its own visibility, so treat the absolute numbers as self-interested, but the underlying claim, that AI systems are being asked software category questions at genuine scale and are answering with specific vendor names, lines up with the buyer-side finding that 82% of B2B software buyers sourced a software recommendation from an AI chatbot at some point in the last two years, a separate figure from G2's July 2026 Buyer Behavior Report.
What are software buyers actually asking AI chatbots?
Mostly comparison and competitor questions, not open-ended discovery. G2's research found that 33% of buyer queries open with a category comparison ("best project management tools for a 20-person team") and 31% start with a competitor-based prompt ("alternatives to X"). Both of those are exactly the queries where a chatbot has to pick which few vendors to name, which means a SaaS brand that is absent from the handful of sources an AI system trusts for that category is absent from the shortlist entirely, not ranked lower on it. AI visibility for B2B brands covers the structural work that applies across industries; for SaaS specifically, the comparison-query pattern is the part worth building content and citations around first.
Which AI tools actually matter most for software research?
Buyers name ChatGPT, Google AI Mode, Perplexity and Gemini as the tools they turn to, but the citation data suggests they do not behave identically. G2's own tracking puts Google AI Mode ahead of the others for citing software review content, with ChatGPT ranking fourth, and a separate analysis by SEO researcher Kevin Indig, covering roughly 30,000 AI citations across ChatGPT, Perplexity and Google AI Mode, found that G2 alone accounts for about 22.4% of citations on software-related queries across those three systems combined. A single review platform carrying nearly a quarter of the citation share on software questions is a concentration a SaaS brand's visibility work has to account for directly, rather than treating all four chatbots as one undifferentiated channel that a generic content strategy will reach evenly.
Does having reviews actually change whether a SaaS brand gets cited?
Yes, and not by a small margin, though the clearest evidence for this comes from outside the SaaS-specific G2 study. A Seer Interactive analysis of 804,491 AI responses found brands with no verified review profile had a median AI citation rate of 1%, against 53.5% for brands with even a minimal one. G2's own data adds a software-specific layer on top of that general finding: it reports that review categories with 10% more reviews see roughly 2% more AI citations, and that G2 profiles with a strong review foundation appear five times more often in AI search answers than thin ones. The practical read for a SaaS company is that an unclaimed or sparsely reviewed listing on the review platforms AI systems actually cite, G2, Capterra, TrustRadius, is a visibility gap with a direct, measurable cost, not a nice-to-have.
What should a SaaS brand actually do about its review profile?
Claim it, keep it current, and ask real customers for reviews on a regular cadence, the same unglamorous work that review platforms have recommended for a decade, except now the audience includes an AI system deciding who makes a shortlist. G2 reports that 45% of buyers in its survey say a review-site citation is the single most confidence-inspiring signal inside an AI-generated answer, ahead of a vendor's own website or marketing claims. That ranking matters for sequencing: a SaaS company putting effort into AI visibility work should treat its review profile as a priority alongside, not behind, the broader structural content work most AI-visibility guidance describes.
What happens when the AI chatbot gets it wrong?
More often than buyers are comfortable with. G2's survey found that 64% of B2B software buyers encounter AI-generated inaccuracies about vendors at least weekly, and only 9% of buyers say they are comfortable letting an AI agent execute a purchase on their behalf even within approved guardrails, a sign that trust in the accuracy of these answers has not caught up with how often buyers are using them. That gap is where a correction strategy matters. AI visibility for fintech brands covers how a regulated industry handles a factual AI error; for SaaS, the stakes are commercial rather than regulatory, but the fix is the same: there is no fast, reliable way to edit what a specific chatbot says about a specific product, so the real lever is strengthening the public record, an accurate G2 or Capterra profile, a clear feature and pricing page, a current comparison page, that the AI system is likely to pull from on the next query.
Does this change how a SaaS company should think about earned media?
It raises the stakes on it rather than replacing it. Earned coverage already accounts for the large majority of AI citations across categories, and software is no exception: a product review in a trade publication, a founder interview, or a comparison piece written by an independent reporter carries the same third-party credibility to an AI system that it does to a human reader. What is specific to SaaS is that the buyer's AI-chatbot conversation now often happens in the same session as the comparison search, which means a company with no recent earned coverage and no claimed review profile can lose a deal to a competitor the buyer had never heard of, entirely inside a single chat window, before a sales team ever gets a chance to compete for it.
The direct answer, for anyone who read this far
AI visibility for SaaS brands runs on the same fundamentals as any other category, earned coverage and structural clarity, but the buyer behavior data from G2's own 2026 research makes the cost of skipping it unusually concrete: half of B2B software buyers now start research with an AI chatbot, most end up choosing a vendor they did not originally plan to, and a third buy from a brand they had never heard of. Claim and maintain a real presence on the review platforms AI systems cite, build content around the comparison and competitor queries buyers are actually asking, and earn coverage that gives an AI system a third-party fact to repeat. If you want a read on how AI assistants currently describe your SaaS product, get in touch with our team.
