92% of B2B buyers say AI shaped their vendor shortlist, yet review sites now outrank chatbots. Here is how to get on the list before sales ever hears of you.
Your next customer may have already picked three vendors before anyone on your team heard from them. According to a Semrush survey of U.S. B2B professionals published in July 2026, 92% of buyers say AI shaped their vendor shortlist, and 45% say it did so significantly.
That changes where go-to-market work has to happen. If your brand is missing when a buyer asks ChatGPT or Gemini for options, no amount of outbound or ad spend fixes the gap later. Here is what the latest data says, and what to do about it this quarter.
What the new buyer research actually shows
Two recent studies are worth reading closely. Semrush surveyed 643 U.S. B2B professionals in March and April 2026. G2 surveyed more than 1,000 software buyers and interviewed over 50 sales and marketing leaders, and published the results in July.
The numbers that matter for your pipeline:
- 97% of Semrush respondents who use AI for work say it helped them discover new vendors, and 66% have noticed vendors missing from AI results.
- 83% say AI influenced their final vendor decision, and 32% say it did so majorly.
- 82% of G2 respondents sourced a software recommendation from an AI chatbot in the last 24 months.
- Review sites (38%) have overtaken AI chatbots (37%) as the top source shaping which vendors make a buyer's shortlist, for the first time.
- Half of the buyers G2 surveyed said AI made its biggest difference when narrowing and comparing options.
Note the method: both are self-reported surveys, and Semrush's findings are based on respondents who use AI tools for work. They show direction, not exact market share. The direction is still hard to ignore.
AI is the opening move, not the closing one
It would be easy to read this as "optimise for chatbots and nothing else." The data says otherwise. Semrush found that 75% of buyers fully or mostly trust AI vendor recommendations, but they still check. After an AI mention, 71% visit the vendor's website, 63% search Google, 46% compare alternatives and 38% look at reviews on sites like G2.
So the AI answer starts a verification trip. Your website, your search presence and your third-party reviews all have to agree with what the model said about you. If the chatbot describes you one way and your homepage says something vaguer, the buyer moves on to the next name.
Why specific beats famous
Here is the finding smaller brands should care about most. Only 7% of Semrush respondents said they notice a vendor because they recognise the name. What earns attention is close use-case fit (53%), a clear description of what you do (50%) and stated benefits (38%). The top complaint about AI recommendations was that they are too generic (33%).
That is good news if you are the specialist. A founder-led B2B services firm that says exactly who it serves and what outcome it delivers is easier for an AI system to match to a query than a big brand with a broad pitch. It also means your positioning is now a visibility asset, not just a messaging exercise. Vague positioning loses twice: with the model and with the buyer.
The evaluation stage is where deals get squeezed
Getting on the shortlist is only the start. G2 found evaluation is now the longest buying stage, longer than research for the first time. IT security review is the biggest delay (39% overall, 50% among enterprise buyers), followed by budget approval (32%).
Finance is also more involved: its role in software decisions rose from 31% to 46% in a year, and nearly half of buyers said a CFO vetoed an approved deal in the last twelve months. G2's advice to vendors is to hand over security documentation, ROI estimates and a CFO-ready business case before they are asked. That is a content and sales enablement job, and it belongs in your go-to-market plan.
A practical plan for this quarter
- Audit what AI says about you. Ask ChatGPT, Gemini, Copilot and Perplexity the questions your buyers ask: best option for [your use case], alternatives to [competitor]. Record whether you appear, how you are described and which sources are cited. Our AI brand visibility audit does this systematically.
- Tighten your positioning to one clear use case per page. Say who it is for, what problem it solves and what result to expect. Rewrite service pages that read like brochures. Website copywriting and GEO optimisation work best together here.
- Build proof outside your own site. Since review sites now edge out chatbots as a shortlist influence, make asking for reviews a routine part of delivery, and keep profiles current.
- Make your own site the best verification stop. Buyers land there after the AI mention. Clear pricing logic, case studies and fast pages matter, and so does solid technical SEO.
- Pre-build the late-stage pack. Security overview, ROI worksheet and a one-page business case for finance. Put it in your CRM so sales can send it the moment a deal reaches evaluation.
- Measure the new path. Add "How did you hear about us?" to forms, and track branded search and direct traffic alongside last-click data. Better channel attribution shows which of these efforts actually feed the pipeline.
Key takeaways
- Most buyers now let AI shape the shortlist before they talk to sales, so absence from AI answers means absence from the deal.
- Buyers verify through your website, Google and reviews, so visibility has to be consistent across all three.
- Specific positioning beats brand recognition: only 7% pick up a vendor by name.
- Evaluation is long and finance-heavy, so prepare your proof before it is requested.
Treat this as one joined-up go-to-market problem, not four separate ones. Positioning, content, SEO and sales enablement all feed the same shortlist. Our go-to-market strategy work is built around exactly that. If you want to know how you currently show up, get a free quote and we will start with an honest look at where AI and buyers find you today.
John Doe
Supreb Information. Thanks
15 July 2014 View replies . 1