Introduction
Over the last few centuries, there have been three major compressions in the buying journey. First, The Yellow Pages collapsed the market into a single book. Then Larry Page's PageRank compressed that book into a single page of results. Now, we're watching the third era of compression unfold in real time. You don't buy the biggest ad or earn the top spot on Google — you win the answer.
What's changed isn't just where buyers start, it's what they're doing throughout the entire journey. They've moved from reference to inference. Instead of weeks of research, they're using ChatGPT to one-shot their shortlists. Today, 51% start their research with an AI chatbot more often than Google, and 71% rely on AI chatbots somewhere in the software research process. The starting point hasn't just shifted. It's split.
G2 has been tracking how software buyers research, evaluate, and choose software for over a decade. This moment feels different because AI chatbots are compressing the research process so dramatically that vendors who don't show up in the first answer are squeezed out before the conversation even starts. We’ve moved past AI as an intelligence layer and are staring squarely at AI as a trust layer.
This report was created to understand exactly what that shift means for software vendors. We polled over 1,000 B2B software buyers and decision-makers and learned that while 93% say AI chatbots have fundamentally changed how they conduct research, AI is not replacing the buying process. Instead, it’s redirecting it in ways that have very specific implications for which vendors get found, trusted, and ultimately, selected.
Key Findings
- 01
The buyer journey has forked.
B2B software research increasingly begins in a chat window. Buyers haven’t stopped Googling, but 71% say they now rely on AI chatbots for software research, up from roughly 60% just 7 months ago. More importantly, half (51%) now start their software research with an AI chatbot more often than Google.
- 02
AI is shaping which vendors win.
In the answer economy, buyers have moved from reference to inference — not asking AI chatbots to point them toward sources, but telling AI to synthesize everything and return a shortlist. Buyers say AI chatbots are the #1 source influencing their shortlist, and 8 out of 10 say those AI chatbots accelerated their purchasing decision. 69% report that AI chatbots have surfaced information that led them to choose a different vendor than expected.
- 03
Review sites are the trust layer in AI search.
Buyers trust recommendations from AI chatbots, but they still want receipts. Trust is increasingly embedded in the answers AI provides, and reviews are its most confidence-inspiring signal. When an answer gives buyers pause, they often seek out peer feedback from communities like G2 and Reddit to verify. For vendors, winning the answer depends on winning the trust layer.
- 04
Buyers aren't experimenting anymore.
Nearly two-thirds of buyers now spend 6+ hours per week using AI chatbots for work, and over 40% self-identify as power users leveraging them daily. Between the adoption of deeper workflows (for example, Deep Research), frequent use of “thinking” modes, and commercial-intent prompts (category comparisons, alternatives, requirements), today’s buyer is using AI search to do serious evaluation.
The buyer journey has forked.
The buyer journey has split into two distinct starting points: traditional search and AI search. More than half of B2B software buyers now say they start their research with an AI chatbot more often than Google. That means the first impression of your brand, category, and competitors is increasingly formed inside an AI answer, before a buyer visits a vendor's website or speaks to their team.
We're no longer watching a trend take shape. AI chat is now a mainstream research motion that B2B software buyers actively use to get oriented, compare options, and narrow the field.
The B2B software funnel increasingly starts with a chat prompt, not a Google search.
AI chatbots have earned a seat in every stage of the funnel. Buyers haven't abandoned traditional search — 80% still use Google somewhere in their buying journey — but they increasingly see it as a complementary function rather than an essential one. Asking a chatbot for answers is now the first move for half of buyers.
That means the first impression of your brand, category, and competitors is often formed inside an AI answer, before a buyer visits a vendor's site or speaks to Sales.
This is a behavioral shift that has reached a tipping point much faster than most vendors expected. As AI search capabilities improve, expect more buyers to become AI-first in their research motion.
AI search is now a one-way door to productivity.
“I'm more productive with AI search than traditional search engines.”
AI didn't just give buyers a new starting point — it drastically improved their outcome. 53% say their software research is more productive with AI search than with traditional search. That number is up sharply from 36% just 7 months ago.
The gains are real. Buyers who once needed weeks to compare vendors can now use their favorite AI chatbot to get a usable synthesis in minutes. And, they don't just start with a prompt. They leverage chat to run comparisons, and ultimately, to decide.
That type of productivity gain is sticky, and it's why usage keeps growing. 86% of B2B buyers increased their use of AI chatbots for software research in the past year.
How has the rise of AI search impacted your software research process?
The best marketing teams we work with aren't asleep. They're just measuring what they've always measured — page rankings, domain authority, click-through rates, etc. The problem is buyer behavior has moved faster than their instrumentation. Buyers are researching in AI now, and most brands have limited visibility into how they show up in those conversations. Even the ones who do have visibility rarely have the tooling to act on it as fast as they'd like.
AI is shaping which vendors win.
This is the Answer Economy. If AI chatbots don't name you in their recommendations, you’re not even in the running. Nearly 7 in 10 B2B software buyers chose a different software vendor than expected in their last buying cycle because of guidance from an AI chatbot. Winning the citation isn’t enough anymore — software vendors need to win the answer.
AI chatbots are the #1 source influencing which vendors make buyer shortlists.
Simply being mentioned by AI chatbots carries weight for today's software buyer, as 85% think more highly of a vendor cited by AI in its answer.
It’s not just perception, though — AI chatbots are curating shortlists and impacting purchasing decisions. 69% of software buyers we polled said that an AI chatbot led them to select a different software vendor than initially planned. 33% purchased from a vendor they'd never previously heard of before.
The same mechanism that lifts an unknown vendor into contention can also exclude a well-known category leader. That is a glaring case to strengthen answer engine optimization (AEO) strategies immediately.
A buyer's first prompt comes with commercial intent.
Buyers who use AI chatbots to research software aren't easing into it. They lead with commercial intent from the very first prompt.
Two-thirds start with category or competitor queries. These are evaluation prompts designed to return a list of best-of-breed vendors buyers can easily evaluate. Only one in five start with questions about requirements or process.
And the process moves fast. Four out of five buyers told us AI chatbots helped accelerate their purchasing decision, and 83% said they felt more confident in their final choice.
8/10 buyers say AI chatbots accelerated their purchasing decision.
When using AI chatbots for software research, 37% reported decisions were much faster and 46% somewhat faster. Only 3% reported a slower process.
AI chatbots changed the outcome for two-thirds of software buyers.
During your most recent software evaluation, did an AI chatbot influence the vendor you ultimately selected?
33% chose a vendor they hadn't considered and 36% chose a familiar vendor after chatbot influence. Another 22% said AI reinforced the expected choice.
Buyers used to spend hours, if not days, cobbling together a spreadsheet and rounds of research, looking for trust signals to winnow down their list to three or four. Now, they one-shot it with an AI chatbot prompt that returns a consideration set before they've visited a single vendor website. They’ve outsourced both the primary research and the synthesis to recommendation engines. Vendors need to stop thinking about AI chatbots as a search channel and start treating them as the new shortlist generator.
Review sites are the trust layerfor AI search.
In the answer economy, trust is the new currency. AI chatbots need verified signals to distinguish from noise, and buyers expect proof that answers are sourced from real human experiences.
Buyers look for review site citations when deciding whether to trust AI search results.
Software buyers trust AI chatbots, but they still want receipts.
When we asked buyers what would increase their confidence in an AI chatbot’s answer, the #1 response was a citation from a review site. That matters because review platforms feed the large language models (LLM) that generate the responses buyers are looking for.
AI chatbots run on peer reviews, and review sites are the #2 source influencing buyer shortlists. Customer voice across review sites like G2 shapes how a chatbot perceives your brand, and what it ultimately returns to buyers.
This effect is strongest among the most experienced AI chatbot users. Self-identified Power users leveraging chatbots daily cite review sites as their #1 confidence signal at an even higher rate (50%) than the general B2B software buyer population. The most AI-fluent buyers show the strongest relative preference for review citations over every other source.
Review sites remain a critical trust signal throughout the buyer journey, along with AI chatbots.
Review sites are the only source besides AI chatbots that gains influence deeper into the funnel.
Review sites aren't just shaping which vendors get discovered — they're contributing to which vendors get chosen. This reinforces why they work as a system. AI chatbots build the shortlist, review sites validate it, and buyers put increasing confidence in both sources as the stakes get higher.
When AI makes a mistake at the brand level, peer reviews are a buyer's gut-check.
AI chatbots get it wrong more often than people realize. In fact, 64% of buyers say they encounter inaccuracies often (a few times per month) or very often (weekly or more). But the pace it enables is too valuable to give up. So, they verify.
When AI chatbots leave out a brand they trust, or get something wrong about one they know, most buyers seek out peer reviews for a second opinion.
Buyers also perceive cross-chatbot consistency as a top trust signal. If ChatGPT, Gemini, and Claude all describe a vendor the same way, that builds confidence, even though the mechanism behind that motion is not something vendors can directly engineer. Inconsistencies represent a red flag to buyers, and they'll dig deeper to find out which version is true.
Review sites are most effective at the bottom of the funnel. When software buyers reach the evaluation stage of their journey, the recommendations they see from AI increasingly stem from trusted peer proof sourced from platforms like G2. With G2’s now significant influence on LLM citations and AI search visibility, there is a strong case for vendors to maintain a steady presence across the G2 ecosystem.
Buyers aren't experimenting anymore.
Nearly two-thirds spend six or more hours a week using AI chatbots for work, and more than 40% identify as daily power users. They're running head-to-head comparisons, creating Deep Research reports, and using Thinking mode for high-stakes evaluations.
Buyers are using AI chatbots for product evaluation, not just discovery.
Primary use cases for AI when researching software.
- Comparing strengths & weaknesses across vendors
- Learning basic category information
- Identifying vendors worth considering
- Validating specific use cases
- Validating an initial recommendation
- Narrowing options to a shortlist
- Drafting RFP questions
- Understanding pricing and packaging
Buyers aren't asking AI chatbots to orient them in a new category. They already know what they're looking for. Comparing vendor strengths and weaknesses is the #1 reason for using AI chatbots in software research, ahead of basic product research, vendor identification, and use case validation.
This clearly illustrates how and where chatbots are gaining ground in software buying. While it’s collapsing the top-of-funnel discovery stage, it’s also extending deeper middle and bottom of the funnel actions. Buyers are using AI chatbots to draft requests for proposals (RFP), work through pricing and packaging options, and validate fit.
41% of buyers use Deep Research tools regularly when researching software. Just 2% have never heard of them.
When we examined the types of AI chat tools buyers were using to conduct software research, most buyers (44%) told us they default to “Thinking” or “Reasoning” models. They deliberately choose these slower, more thorough output options when the decision matters.
But, research tools like Deep Research are more popular than people realize. Just 6% of buyers said they don’t use Deep Research — which generates structured, multi-source evaluation reports in minutes. This high adoption further indicates that today’s buyer is running complex, multi-source evaluations with AI search.
When asked how it holds up next to standard models, nearly half of buyers said the output from Deep Research is meaningfully better. These are real evaluation workflows that now live inside a chatbot, rather than being shared by a handful of employees on the project team.
ChatGPT dominates, but the AI chatbot landscape is shifting fast.
ChatGPT is the most popular AI chatbot across every segment — but mid and bottom funnel chatbot usage is more competitive.
ChatGPT is the dominant AI chatbot for work, and its usage is concentrated at the top of the funnel. But, the landscape is shifting fast — Claude more than doubled its share in the past seven months, while Copilot and Perplexity both declined sharply. Meanwhile, the race for second place is wide open. Gemini nearly doubles its share between discovery and consideration, and Copilot, Claude, and Perplexity all hold steady or gain ground as buyers move deeper into the funnel.
ChatGPT is the top AI chatbot across every segment — but secondary preferences vary by industry and company size.
Both tables are shown when JavaScript is unavailable.
| ChatGPT | 61% | 65% | 53% | 57% | 66% | 54% | 66% |
| Gemini | 14% | 14% | 23% | 28% | 16% | 24% | 21% |
| Copilot | 10% | 7% | 10% | 8% | 5% | 11% | 6% |
| Claude | 8% | 10% | 10% | 3% | 6% | 2% | 6% |
| Perplexity | 2% | 2% | 2% | 2% | 2% | 5% | 0% |
| Financial services | Healthcare | Manufacturing | Retail | Technology | Services | Construction |
|---|
| Chatbot | SMB | Mid Market | Enterprise | Large Enterprise |
|---|---|---|---|---|
| ChatGPT | 58% | 62% | 70% | 57% |
| Gemini | 21% | 19% | 14% | 18% |
| Copilot | 6% | 8% | 10% | 13% |
| Claude | 7% | 7% | 3% | 6% |
| Perplexity | 2% | 1% | 1% | 3% |
ChatGPT leads across every industry and company size, but the margins vary. In manufacturing, ChatGPT's lead shrinks to nearly 10 points below its average while Gemini picks up 23%. Construction shows a similar pattern. In enterprise and large enterprise environments, Copilot holds a 10–13% share, which may be driven by Microsoft's bundled distribution through Microsoft 365. Claude's strongest showing is in the small business (SMB) sector (7.3%), which tracks with its reputation among technical early adopters.
ChatGPT is the default at every level, but technical roles show more diverse chatbot usage.
Both tables are shown when JavaScript is unavailable.
| ChatGPT | 58% | 61% | 66% |
| Gemini | 18% | 18% | 23% |
| Copilot | 8% | 9% | 4% |
| Claude | 8% | 6% | 3% |
| Perplexity | 3% | 2% | 2% |
| Individual contributors | Manager / Director / VP | C-Suite |
|---|
| ChatGPT | 64% | 68% | 62% | 56% | 62% | 51% | 49% |
| Gemini | 16% | 17% | 18% | 16% | 23% | 25% | 29% |
| Copilot | 9% | 9% | 9% | 10% | 7% | 9% | 10% |
| Claude | 4% | 4% | 8% | 9% | 5% | 12% | 5% |
| Perplexity | 2% | 0% | 2% | 2% | 0% | 1% | 0% |
| IT | Senior mgmt | Finance | Procurement | Operations | Engineering | Support |
|---|
- C-suite executives are the most ChatGPT-dominant group, but the role-level data tells us a few interesting stories.
- Engineering/R&D shows the most diverse chatbot usage, including Claude reaching its highest share in any function.
- This suggests that the more technical or evaluation-heavy the role, the more likely buyers are to use multiple tools.
- For vendors, this means the person comparing you in ChatGPT may not be the same person running the Deep Research report in Claude — but both of their impressions matter.
“While working with AI to aid evaluation, we include questions related to feature depth, scalability, pricing models, and performance, and cross-check answers with other AI tools for consistency.”
“I ask AI to compare vendors side by side, break down pricing, highlight pros and cons, and simulate use cases. What used to take days now takes a few hours, though I still validate key decisions manually.”
What GTM leaders are already seeing
Using G2's AI Custom Research solution, we conducted interviews with 39 B2B software marketers globally, exploring their experiences with the rise of AI-driven search and how they’re adapting.
- 01
Most marketers know AI discoverability matters, but most aren't ready.
Nearly every respondent called it a "must-have" for pipeline. Yet, the majority described themselves as early-stage or still figuring out their approach, with competing internal priorities slowing them down. Respondents reported measurable declines in organic search traffic — some significant — while LLM-sourced traffic ticked up. For many, seeing their own name missing from AI-generated results was the moment they took it seriously.
- 02
Reviews are showing up in AI-generated answers, and marketers are responding.
Several respondents independently observed AI chatbots pulling from review sites when generating vendor recommendations. In response, some are actively coaching customers to write more detailed, context-rich reviews — specifically noting what problems were solved and what alternatives were considered.
- 03
Prompt-testing has become a DIY competitive intelligence practice.
Across maturity levels, respondents described regularly typing buyer prompts into ChatGPT, Gemini, and Perplexity themselves to see whether they appear, who shows up instead, and using those gaps to guide their content priorities.
- 04
Attribution is the loudest, most consistent frustration.
Respondents at every stage described the same problem: They can see signals that AI chatbots are influencing pipeline, but they can't measure it cleanly. Many described it as investing in a channel they can't yet prove.
- 05
Adaptation is happening, but it's largely tactical and fragmented.
The most common tactics marketers told us they’ve embraced are content restructuring (FAQ format, answer-first writing, comparison pages) and increased review generation, but few described a fully integrated, scalable strategy.
What can vendors do to win the AI answer?
The vendors who win in the era of AI-powered search will be the ones who invest in the trust infrastructure that AI depends on. Here are three things you can do today.
- 01
Collect reviews at all stages of the buyer journey.
Look for ways to engage your customer/buyer community in an always-on fashion – requesting they submit reviews for your products through ongoing review campaigns, in-app review collection, and after any standard customer touchpoint.
- 02
Ensure your profiles feature the most accurate content and positioning.
Think beyond your owned properties on your website and consider your social media profiles, your Glassdoor page, your G2 Profile listings. While you can’t control 100% of how your brand is portrayed by LLM answers, take ownership of what you can impact by ensuring an accurate representation of your company and products on any profile page you have access to.
- 03
Develop a sound AEO strategy to optimize content and measure impact.
Use an AEO tool or agency to help understand how you’re showing up in AI search platforms today, and to also identify the prompts your buyers are asking. From there, create content that addresses buyer questions, increasing your likelihood of showing up as a top source in future AI answers.
Methodology
G2 fielded an online survey among 1,076 B2B decision makers responsible for, or influencing, purchase decisions for departments, multiple departments, operating units, or entire businesses. Respondents had job titles ranging from individual contributor to manager, director, vice president, or higher.
To maximize differentiation for vendors, this survey defines small-medium business (SMB) as a company with 1-250 employees, mid-market as a company with 250-1,000 employees, enterprise as a company with 1,000-5,000 employees, and large enterprise as a company with 5,000+ employees. The survey was conducted in March 2026 and includes a global pool of respondents across North America, EMEA, and APAC.
Qualitative research was conducted through over 39 interviews with B2B software marketers through G2’s AI Custom Research (AICR). Generative AI reasoning models were used to define the study’s focus areas, optimize survey design, and analyze results to inspire writing and data visualizations.
About G2
G2 is the world’s largest and most trusted data source for B2B software, helping businesses reach their peak potential by enabling confident buying and go-to-market decisions. Offering trusted data, authentic peer reviews, and real-time market intelligence, the G2 ecosystem — which includes Capterra, Software Advice, and GetApp — serves more than 200 million annual buyers, representing teams at every Fortune 500 company.
As buyers increasingly shift from traditional search to AI search platforms, G2 has become the most-cited B2B software source across those AI-first channels where software discovery happens. Leading software and services companies like Salesforce, IBM, SAP, Adobe, and Clay also trust G2 to influence discovery, build brand credibility, reach in-market buyers, and accelerate revenue growth. To learn more, visit www.g2.com and follow us on LinkedIn.