We Asked 5 AI Engines the Same 20 Questions. They Disagreed on the #1 Answer 50% of the Time.

AI search engines agree on the #1 brand recommendation in only 50% of B2B software queries. Of 20 queries sent to ChatGPT, Perplexity, Gemini, Grok, and Claude, just 6 (30%) produced unanimous agreement on which brand to recommend first. In the other half, engines gave different top picks, sometimes wildly so: one query produced four different #1 answers from four different engines.

We have now run these same 20 queries across three weekly waves. The consensus rate oscillated: 50% in Wave 1, 55% in Wave 2, back to 50% in Wave 3. The engines are not converging on stable answers. They are oscillating, and single-wave trends are unreliable.

If you are optimizing your AI search presence based on what a single engine tells you, you are working with a coin flip's worth of the picture. The other engines may be recommending your competitor.

The Study: 20 Queries, 5 Engines, 25 Brands

We ran 20 B2B software queries across 5 AI search engines (ChatGPT, Perplexity, Gemini, Grok, and Claude) via real-time API calls, simulating how actual buyers interact with these platforms. We tracked 25 B2B SaaS brands across 5 categories: CRM, Project Management, Email Marketing, Analytics, and Dev Tools. For each query, we recorded which brand each engine placed at position 1.

The goal was simple: when a buyer asks an AI engine "what's the best tool for X," does it matter which engine they ask?

It does. Significantly.

The Data: Cross-Engine Agreement Is the Exception, Not the Rule

Here is the full position-1 breakdown for all 20 queries. Each cell shows which tracked brand the engine recommended first.

Six queries now achieve unanimous agreement, up from 4 in Wave 1: "alternative to Mailchimp," "alternative to Google Analytics," "analytics comparison," "analytics for startups," "Vercel vs Netlify," and "best hosting for Next.js." These are queries with a single dominant brand where the answer is nearly tautological.

The moment the query gets competitive, consensus breaks down.

Disagreement by Category: PM and Analytics Are a Free-for-All

Not all categories are equally fragmented. CRM and Dev Tools have clear leaders that most engines agree on. Project Management and Analytics are battlegrounds.

Project Management is the most contested category in AI search, and it is getting worse. No PM brand has achieved even majority consensus (3/5) on any query in any of the three waves we have measured. When we asked "best project management tool for engineering teams," all five engines gave different answers. A marketing director checking only ChatGPT would conclude one brand is the winner. They would be wrong.

Analytics tells the opposite story. Over three waves, analytics consensus improved from 1/4 to 3/4 queries with strong agreement. Amplitude now holds unanimous 5/5 consensus for "analytics comparison," and Google Analytics locks 5/5 for "analytics for startups." The window for analytics challengers is closing rapidly.

How Different Are These Engines, Really?

We measured pairwise overlap: the percentage of brand mentions shared between any two engines across all 20 queries.

ChatGPT and Gemini now share the lowest overlap at 58%, the lowest pairwise agreement in the entire three-wave dataset. ChatGPT is increasingly diverging from the other engines: it dropped ActiveCampaign entirely from email marketing responses in Wave 3, gave Netlify its first-ever #1 position, and is the only engine that heavily cites Wikipedia (10.4% of its URLs). Meanwhile, Grok and Claude converged to the highest agreement pair at 75%.

The pairwise overlap floor has oscillated across three waves: 58% (W1), 63% (W2), 58% (W3). The engines are not settling into agreement. They are forming shifting alliances.

The practical implication: optimizing for one engine guarantees nothing about another. A brand that ranks well in Perplexity has roughly a 60-70% chance of appearing in other engines for the same query, and even then, not necessarily at the same position.

Supporting Evidence: What the Engines Actually Said

The disagreements are not subtle ranking differences. They are fundamentally different recommendations.

When we asked "best analytics tool for SaaS," ChatGPT led with PostHog, describing it as ideal for "product-led growth startups" and citing its open-source model. Perplexity led the same query with Amplitude, a larger and more established company. Gemini also went with Amplitude. Claude chose Mixpanel. Three different first picks from five engines.

For "what PM software should I use," Asana, Monday.com, and ClickUp all claimed the top spot depending on the engine. No brand got more than 2 out of 5 first-place finishes.

The most contentious query was "best project management tool for engineering teams," where four engines gave four different #1 answers and one engine mentioned zero of our tracked brands entirely. A buyer using Claude for this query would not even encounter Monday.com, Asana, or Linear, the three brands fighting for position in the other engines.

What This Means

Single-engine monitoring is incomplete by design. If you check your brand's position in ChatGPT and call it a day, you are seeing at best 60% of what AI search actually looks like. The other 40% might be recommending your competitor. As of March 2026, no two AI engines agree on more than 75% of brand mentions for the same queries, and the lowest pair (ChatGPT-Gemini) agrees on only 58%.

Fragmented categories are the biggest opportunity, but the windows shift. In Wave 1, CRM and Dev Tools looked locked in. By Wave 3, CRM consensus cracked from 75% to 25%, while Analytics solidified from 25% to 75%. Project Management remains maximally fragmented with 0% consensus for two consecutive waves. Categories that look settled can destabilize, and vice versa. Multi-engine AEO monitoring must be continuous, not periodic.

Each engine has its own sourcing bias. ChatGPT pulls heavily from brand-owned websites. Grok favors third-party reviews and Reddit. Perplexity and Gemini lean on aggregators and tech publications. A single content strategy aimed at one source type will perform unevenly across engines.

Position 1 is not the same as presence. Several brands in our study appeared in all five engines but never once claimed the top spot. Being mentioned is table stakes. Being recommended first is what shapes buyer consideration.

What You Can Do About It

• Monitor all five major AI engines simultaneously. Checking one engine gives you a partial, potentially misleading picture. You need to see your position across ChatGPT, Perplexity, Gemini, Grok, and Claude for every query that matters to your category.
• Identify which categories are fragmented in your space. If engines disagree on the #1 brand for your target queries, there is an opening. If they agree on an incumbent, your strategy needs to be different.
• Tailor content to each engine's source preferences. ChatGPT rewards strong brand-owned content (pricing pages, documentation, feature comparisons). Grok rewards third-party coverage and Reddit presence. A platform that checks all engines can show you where each engine is pulling its information from.
• Track position, not just presence. "We appear in AI search" is not a useful metric. "We are recommended first by 3 of 5 engines for our primary buyer query" is. Position tracking across engines is the only way to measure real AI search performance.
• Recheck frequently. AI engine recommendations shift as models update and new content enters the retrieval set. A 48-hour monitoring cadence catches position changes before they compound.

Methodology

We ran 20 queries across 5 AI search engines (ChatGPT, Perplexity, Gemini, Grok, and Claude) over three weekly waves in March 2026. Each query was sent as a real-time API call, simulating how actual users interact with these platforms. We tracked 25 B2B SaaS brands across 5 categories (CRM, Project Management, Email Marketing, Analytics, Dev Tools), recording which brand each engine placed at position 1 and all citation URLs in each response. The data table above reflects Wave 3 (the most recent wave). Three-wave trends are noted throughout the article.

Frequently Asked Questions

How often do AI search engines agree on the best B2B software recommendation?

As of March 2026, AI search engines reach unanimous agreement (all 5 engines recommending the same #1 brand) in 30% of B2B software queries. Strong consensus (4 or more engines agreeing) occurs in 50% of queries. That 50% rate has oscillated across three weekly waves (50%, 55%, 50%), showing the engines are not converging toward agreement.

Which AI engine is most different from the others?

ChatGPT and Gemini share the lowest pairwise overlap at 58%, the lowest agreement between any two engines across all three waves of our study. ChatGPT is diverging from the other engines, using Wikipedia heavily and making unique editorial decisions (like dropping ActiveCampaign entirely from email responses). Grok and Claude are now the most similar pair at 75% overlap.

Which B2B software categories have the most disagreement across AI engines?

Project Management is the most fragmented, with 0% consensus across two consecutive waves. Analytics has moved in the opposite direction, improving from 25% to 75% consensus over three waves. CRM, which looked stable at 75% in Waves 1 and 2, cracked to 25% in Wave 3. Category consensus is not static.

Does optimizing for one AI engine help with the others?

Partially. Engines share 58-71% of their brand mentions, so improvements in one engine may carry over. But position rankings differ significantly. A brand can be #1 in ChatGPT and #3 in Perplexity for the same query. Multi-engine monitoring is required to understand your actual visibility.

How many AI engines should a brand monitor?

All five major engines: ChatGPT, Perplexity, Gemini, Grok, and Claude. Our data shows that no single engine is representative of the full AI search landscape. Brands that monitor only one engine are working with an incomplete, and potentially misleading, picture of their AI visibility.

Related Resources

• Multi-Engine AEO: Why Optimizing for One AI Engine Isn't Enough
• We Analyzed Citations Across 5 AI Engines: Here's What We Found
• The 5 Major AI Search Engines and How They Cite
• My Startup Is Invisible to AI Search: Here's How to Fix It