No. AI search is not replacing Google. Google still processes over 8.5 billion searches per day, and 85% of consumers who use AI search still cross-reference answers through Google before purchasing. But for a specific and growing category of queries, the ones where buyers ask "which is best," "what should I use," or "compare X vs Y," AI search engines are already the primary channel. ChatGPT handles 84 million shopping queries per week. AI referral traffic converts at 15.9% versus 1.8% for Google organic. Agencies that frame this as an either/or question are asking the wrong thing. The right question is which query types are moving to AI, and whether your clients show up when they do.
This article covers what is actually shifting, what is staying on Google, how buyer behavior has changed in ways that affect agency delivery, and what agencies should build now to cover both channels without doubling their workload. For a brand-focused version of this analysis, see Is ChatGPT Replacing Google for Buying Decisions?.
The Bottom Line
- AI search is supplementing Google, not replacing it. The two channels serve different stages of the buying journey.
- For recommendation queries ("best X for Y," "which tool should I use," "X vs Y"), AI search engines are already the first stop for a growing share of buyers.
- Agencies that only offer SEO are covering one channel. The agencies adding AI search optimization are covering both, and keeping a larger share of client spend.
What Is Actually Moving to AI Search
Recommendation, comparison, and evaluation queries are migrating fastest. When a buyer asks "best CRM for a 15-person remote team with Slack integration," they increasingly ask an AI search engine first. The AI returns a ranked list with reasoning. The buyer then goes to Google to verify pricing, read reviews, and complete the transaction.
The query types that have shifted
Three categories of queries have moved substantially toward AI search engines as of mid-2026:
"Best X for Y" queries. These are the queries where a buyer has a specific need and wants a shortlist. "Best accounting software for agencies," "best project management tool for engineering teams," "best AEO platform for small business." AI search engines handle these well because the conversational format lets the buyer add constraints that keyword search cannot express. A buyer can follow up with "but which one is cheapest" or "which one has a free tier" and get refined answers without starting a new search.
Comparison queries. "HubSpot vs Salesforce for small teams," "Asana vs Monday.com for marketing agencies." AI search engines synthesize information from multiple sources and present a structured comparison. The buyer does not need to open five tabs and read five articles. The AI does that synthesis.
"Should I" and "is it worth" queries. These are evaluation queries that signal a buyer is close to a decision but needs validation. "Should I switch from Mailchimp to ConvertKit," "is SEMrush worth it for a small agency." AI search engines provide opinionated answers with reasoning, which is exactly what these buyers are looking for.
What to do: Map your clients' buyer journeys and identify which queries fall into these categories. Those are the queries where AI search visibility matters most. If a client's buyers ask "best X for Y" questions, and your client is invisible in AI answers, the competitor who shows up gets the consideration. The client does not just lose a ranking. They lose inclusion in the conversation entirely.
What is staying on Google
Navigational queries ("HubSpot login," "G2 reviews"), transactional queries ("buy running shoes," "book hotel downtown"), and highly local queries ("plumber near me") are still overwhelmingly handled by Google. These are queries where the user already knows what they want and needs to get somewhere or complete a purchase. AI search engines add friction to these actions rather than reducing it.
Google also remains dominant for "verify and transact" behavior. Even when a buyer discovers a brand through AI search, they typically Google the brand name afterward to check the website, read reviews, and compare pricing. This means SEO still matters for the bottom of the funnel. It just no longer owns the top.
What to do: Do not position AI search optimization as a replacement for SEO work. Position it as the layer that covers the queries SEO misses. When a client asks "do I still need SEO," the answer is yes: SEO covers discovery through Google, transaction support, and brand verification. AI search optimization covers the recommendation and comparison layer where buying decisions are increasingly being shaped.
How Buyer Behavior Has Changed
The shift is not just about which platform buyers use. It is about how they search. AI search has introduced behavioral patterns that change what content needs to exist and how agencies need to think about client visibility.
Queries are 3x longer and full of constraints
The average AI search query is three times longer than a traditional Google search. Instead of typing "CRM software," buyers type "best CRM for a bootstrapped B2B startup with 5 salespeople and a HubSpot integration." Each additional constraint narrows the field and increases the specificity of the AI's recommendation.
For agencies, this means the content that gets clients recommended must match these specific combinations. A generic "Best CRM Software" page might rank on Google but will not earn an AI recommendation for a query with four constraints. The content needs to address specific use cases, team sizes, integrations, and budget ranges.
What to do: Pull your clients' sales call transcripts and support tickets. The questions prospects actually ask contain the constraints AI search users are typing. Build content that answers those specific multi-constraint questions. This content serves double duty: it ranks on Google for long-tail queries and earns AI recommendations when the constraints match.
Multi-turn conversations replace single searches
Follow-up queries in Google AI Mode grew 40%+ per month. Buyers do not ask one question and stop. They ask a question, get an answer, then drill deeper. "Best project management tool for remote teams" is followed by "which one is cheapest" is followed by "does it integrate with GitHub" is followed by "what do people on Reddit say about it."
Each follow-up triggers the AI search engine to research the candidate brands more deeply. If a client's content answers the first query but does not contain pricing information, the client drops out of the conversation at the second turn. If it does not mention integrations, the client disappears at the third turn.
What to do: Every client page that targets a recommendation query must contain the attributes buyers ask about in follow-up turns: pricing, integrations, team size fit, comparison to alternatives, and user sentiment. AI search engines independently research each candidate brand against these attributes. Missing any one of them means losing the recommendation at a later stage of the conversation.
The "verify through Google" loop
85% of consumers who use AI for search still cross-reference those answers through Google. This creates a two-channel loop: discover through AI, verify through Google. A brand that appears in ChatGPT's recommendation but has a weak Google presence (no reviews, no comparison content, thin product pages) may lose the deal at the verification stage.
What to do: Audit clients for both channels. Check what AI search engines say when buyers ask recommendation queries. Then check what Google shows when buyers search the client's brand name. If either channel has gaps, the handoff between AI discovery and Google verification breaks down. The agency that covers both channels delivers a complete buyer journey.
What "Only Offering SEO" Leaves on the Table
An agency that offers SEO but not AI search optimization is covering a shrinking share of how buyers discover and evaluate products. The share is shrinking not because Google is dying, but because the queries with the highest purchase intent are splitting across two channels.
The third-party source gap
SEO agencies optimize client websites. But 85% of AI citations come from third-party sites, not brand websites. Only 6.3% of 1,122 citation URLs in Loudmink's research pointed to tracked brand domains. The sources AI search engines actually use, review sites, Reddit threads, YouTube videos, and editorial articles, are not typically in an SEO agency's scope.
This creates a service gap. The client's website is optimized. Their Google rankings are strong. But AI search engines are forming recommendations based on what G2 reviewers, Reddit users, and comparison bloggers say about them, not what their own product page says. An agency that manages those third-party channels for AI visibility is covering territory that SEO-only agencies leave empty.
The per-engine complexity
Different AI search engines behave differently. Does your Google ranking affect ChatGPT recommendations? Only indirectly, because ChatGPT retrieves through Bing, not Google. Grok cites Reddit 13x more than other AI search engines. Perplexity favors editorial and review content. Claude penalizes promotional language. Each engine has its own source preferences, citation behaviors, and content biases.
An SEO agency that adds "we'll check ChatGPT too" is not delivering AI search optimization. Genuine AI search optimization requires monitoring across multiple engines, understanding per-engine source preferences, and creating content tailored to how each engine retrieves and evaluates sources. This complexity is what makes AI search optimization a distinct service line rather than an SEO add-on.
What to do: If your agency currently offers only SEO, you do not need to abandon it. SEO remains the foundation for AI visibility because AI search engines retrieve content through Google and Bing. But layer AI search monitoring and multi-channel content strategy on top. The margin is favorable: AEO platforms start at $99/mo per client, and retainers for the combined service range from $1,500 to $15,000/mo. For operational details on building this service line, see AI search for agencies: what it is and why it matters.
What Agencies Should Build Now
The agencies that will own this category are building four capabilities: multi-engine monitoring, third-party content strategy, client education, and measurement frameworks.
Multi-engine monitoring
Track what AI search engines say about each client across at least three engines. ChatGPT, Perplexity, and Gemini cover the broadest range of buyer behavior. AI search engines disagree on the top recommendation in 50% of B2B queries, so single-engine monitoring produces reporting that is wrong half the time.
As of June 2026, AEO platforms like Loudmink offer multi-engine monitoring starting at $299/mo (ChatGPT, Gemini, Perplexity on the Pro plan) and $599/mo for all five engines on the Max plan. The platform cost per client is low enough that agencies maintain 70% to 80%+ margins even on mid-market retainers.
Third-party content strategy
Build client presence on the sources AI search engines actually cite: review platforms (G2, Capterra, Trustpilot), Reddit discussions in the client's category, YouTube videos covering the client's space, and editorial articles that mention the client in comparison or "best of" contexts. This is where the 85% of citations that do not come from brand websites originate.
Client education
Most clients do not understand AI search yet. The agency that can run a 15-minute diagnostic (search the client's buying queries across ChatGPT, Perplexity, and Gemini, and show them who appears), explain why competitors are showing up, and present a plan to fix it has a pitch that no SEO-only agency can match.
Measurement frameworks
Define how you will report on AI search performance. Track recommendation position by engine, citation sources, content that earned recommendations, and changes over time. AI search does not show up in Google Analytics the way organic does. Agencies need dedicated monitoring to demonstrate the value of the work.
What to do: Start with one or two clients as a pilot. Run the diagnostic, present findings, deliver initial content, and measure whether AI recommendations change. Build the case study, then roll the service out to the rest of your client base. The first mover advantage is real: agencies building this capability now will have operational experience and proven results when every agency is scrambling to add it in 18 months.
The Honest Answer: Both Channels Matter
AI search is not replacing Google. It is creating a second discovery channel that operates on different mechanics, favors different sources, and serves different stages of the buying journey. Google still dominates volume. AI search is winning on intent and conversion.
For agencies, the strategic question is simple. Do you want to be the agency that covers one channel, or both? SEO is not going away. But SEO alone no longer covers how buyers discover, evaluate, and choose products. The agencies that add AI search optimization now are not betting against Google. They are covering the full buyer journey and capturing the revenue that comes with it. Agencies that care about AI search and act on it now are positioning themselves for a category that will only grow.
Frequently Asked Questions
Is AI search actually replacing Google?
No. Google processes over 8.5 billion searches per day and remains dominant for navigational, transactional, and verification queries. AI search is supplementing Google for recommendation, comparison, and evaluation queries. The two channels serve different stages of the buying journey, and 85% of AI search users still cross-reference through Google before purchasing.
Should agencies stop offering SEO?
No. SEO remains the foundation for AI visibility because AI search engines retrieve content through Google and Bing. A client that does not rank on Google is also invisible to AI search engines. The opportunity for agencies is not to replace SEO with AI search optimization but to layer AI search optimization on top of existing SEO services, creating a more complete offering and a higher-value retainer.
Which query types are most affected by AI search?
Recommendation queries ("best X for Y"), comparison queries ("X vs Y"), and evaluation queries ("should I switch to X," "is X worth it"). These are the query types where buyers increasingly ask AI search engines first, get a shortlist, and then verify through Google. Navigational, transactional, and highly local queries remain primarily on Google.
How is AI search optimization different from SEO?
SEO optimizes for ranking on Google's results page. AI search optimization adds a layer: understanding which queries AI search engines generate behind the scenes (query fan-out), building presence on the third-party sources AI engines cite (only 6.3% of citations come from brand websites), monitoring across multiple AI search engines (which disagree 50% of the time), and creating content structured for AI extraction and recommendation. The underlying content craft is the same, but the monitoring, distribution, and measurement are distinct.
What does it cost an agency to deliver AI search optimization?
AEO platforms start at $99/mo per client for single-engine monitoring and content execution. Multi-engine monitoring with Reddit and YouTube coverage is available at $299 to $599/mo per client through the Loudmink agency partner program. At retainers of $1,500 to $15,000/mo, agencies maintain 70% to 80%+ gross margins, which is significantly better than most SEO engagements where content production costs eat into margins.