The 2026 State of B2B Buying: Half Your Buyers Start in an AI Chatbot
In March 2026, G2 surveyed 1,076 B2B software buyers and found that 51 percent now start their research in an AI chatbot more often than Google, up from 29 percent a year earlier. AI is building the shortlist before your sales team is involved: 69 percent of buyers chose a different vendor than planned based on AI guidance, and one in three bought from a vendor they had never heard of. If your brand is not in the answer, you are not in the running, which makes answer engine optimization a demand-gen priority, not a side project.
Half of your B2B buyers now begin their software research inside an AI chatbot, not on Google. In March 2026, G2 surveyed 1,076 B2B software buyers and decision-makers and found that 51 percent start their research with an AI chatbot more often than with Google, up from just 29 percent a year earlier. That is the fastest behavioral shift G2 says it has measured in more than a decade of tracking how software gets bought.
If you run demand gen, this is the most important number on your desk in 2026. The first impression of your brand is increasingly formed by what an AI says about you, before a buyer ever sees your website or talks to your team.
What does the G2 data actually say?
The headline is the starting line, but the rest of the data is where it gets serious. According to G2's report, "The Answer Economy", the picture for B2B software buying now looks like this:
- 51 percent start research in an AI chatbot more often than Google, up from 29 percent in 2025.
- 71 percent rely on AI chatbots at some point in their research process.
- 61 percent use AI search alongside Google in tandem, so this is augmentation, not pure replacement.
- 53 percent say AI research is more productive than traditional search, up from 36 percent seven months earlier.
- 41 percent now use Deep Research tools for structured software evaluations, returning 10 to 20 page reports rather than a quick answer.
Buyers are not asking AI to point them at sources anymore. As G2 puts it, the shift is from reference to inference: buyers tell the chatbot to synthesize everything and return the best options. The independent reporting on the survey via Demand Gen Report frames it the same way — the research phase has moved off your site and into the model.
Why is AI building the shortlist before you know it exists?
This is the part that should change how you allocate budget. AI is not just helping buyers learn; it is curating the consideration set.
G2 found that AI chatbots are now the top source influencing buyer shortlists, ahead of review sites, analyst firms, and vendor websites. And the downstream effects are large:
- 69 percent of buyers chose a different vendor than they had initially planned, simply because it surfaced in the chatbot's recommendation.
- One in three purchased from a vendor they had never previously heard of.
- 85 percent of buyers think more highly of a vendor when an AI includes it in an answer.
Read those together and the logic is blunt. If the model names you, you gain credibility and you enter the consideration set. If the model leaves you out, the buyer may never learn you exist. As G2's analysis puts it, if AI chatbots are not naming you in a recommendation, you are not in the running. Discovery, shortlisting, and evaluation are increasingly happening inside the AI, and buyers arrive with commercial intent from the very first prompt.
What does this mean for demand gen?
The instinct for many teams is to keep optimizing the same things: page rankings, domain authority, click-through rates. Those signals tell you almost nothing about how ChatGPT describes your company or whether Gemini includes you in an answer. The job has changed.
This is where answer engine optimization, or AEO, becomes a core demand-gen discipline rather than a curiosity. SEO is built to win the click; AEO is built to win the answer. If you are not yet clear on the distinction, our primer on what AEO is is a useful starting point. The short version: optimizing for AI answers means earning a place in the recommendation itself, not just a ranking on a page that buyers increasingly skip.
Three priorities follow directly from the G2 data, and they map onto how we approach SEO and AI search:
Own your external message. Models draw from a far wider surface than your website. They read your third-party profiles, your category positioning, your social presence, and independent coverage. You cannot control everything an AI says about you, but you can control the inputs. Accurate, specific, and consistent positioning across every property you own is a direct competitive advantage, because models treat consistency across ChatGPT, Gemini, and Claude as a trust signal. When the descriptions conflict, buyers dig in to find the truth, and inconsistency reads as a red flag.
Invest in third-party proof. Buyers trust AI recommendations, but they want validation. G2 found that citations from a software review site are the top trust signal increasing buyer confidence in an AI answer, and that review sites are the one source besides AI chatbots that gains influence deeper into the funnel. Reviews do not just persuade buyers directly; they feed the models the trust signals that determine whether you get named at all. Thin or stale review presence gives an AI less reason to recommend you over a competitor.
Build content around real prompts. Most teams still write for keywords. AEO means identifying the actual questions your buyers ask a chatbot, including head-to-head comparisons and bottom-of-funnel evaluation prompts, and creating content that answers them directly and specifically. With 41 percent of buyers running Deep Research evaluations that span 10 to 20 pages, a single buried citation does not win the deal. Being one of the recommended brands at the end of that report does.
How do you know if you are winning the answer?
You measure it. The most proactive marketers in G2's research have turned prompt engineering into a competitive-intelligence habit: they regularly type buyer queries into ChatGPT, Gemini, and Perplexity to see who shows up and who does not. That is the new baseline diagnostic, and it belongs in your performance reporting alongside traditional pipeline metrics. Organic search traffic is trending down while LLM-sourced traffic is trending up, and if you are not tracking the second, you are flying blind on half the funnel.
Start simple. Pull your ten most important buyer prompts, run them across the major chatbots, and log three things: are you named, what do they say, and is the story consistent across models. That single exercise will tell you more about your 2026 demand-gen exposure than another month of keyword rankings.
The buyers in your pipeline are already using AI to evaluate you. As G2 puts it, the only real question is whether you will be in the answer when they look. The teams building for that now are opening a structural lead that late movers will spend years trying to close.
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51 percent, according to G2's March 2026 survey of 1,076 B2B software buyers. That is up sharply from 29 percent in G2's 2025 report. A further 71 percent rely on AI chatbots at some point in their research, and 61 percent use AI search alongside Google rather than replacing it outright.
