What Does an AI SEO Agency Do and What Should It Cost? A Guide to GEO, AEO, and Social Search Optimization Companies in 2026

A plain-language guide to what agencies charge, what the work looks like, and what to ask before you sign anything.

I keep getting the same question from business owners, current colleagues and people just trying to contextualize what AI mediated search is. Not in those words, exactly. It usually starts with something like: my traffic is down and my team can't explain it, or, a client told me they found our competitor through ChatGPT, or, someone on my board keeps saying we need to be doing AI SEO and I don't know what that means yet.

The honest answer is that search changed structurally over the last two years in ways that affect how every business gets discovered. The short version: Google is no longer the whole picture. AI platforms like ChatGPT, Perplexity, Claude, and Google's own AI Overviews now generate synthesized answers that cite a handful of sources instead of returning a page of links. Social platforms became search engines with their own algorithms and their own rules for visibility. The infrastructure that determines whether your business gets found, what I call the retrieval layer, now spans all of it.

I've written extensively about what that shift looks like and what it means. This piece is about something more specific: what happens when you decide to hire someone to help you navigate it.

Because the market for AI SEO agencies already exists, even if most business owners don't know it yet. Agencies have published pricing. Tools have raised serious venture capital. The terminology is messy but the services are real. The problem is that the range of what's being sold under the AI SEO label is enormous. Some of it is genuine, specialized work. Some of it is traditional SEO with new vocabulary stapled to the invoice. And the pricing spread is wide enough that without some frame of reference, it's hard to know whether you're looking at a bargain, a fair rate, or an expensive repackaging of work that stopped being sufficient two years ago.

Some context on where I'm coming from. I've been doing SEO since 2004, working both agency-side and in-house across industries like luxury hospitality, e-commerce, SaaS, skincare, travel, and agribusiness, in markets from California to Canada to the Caribbean to Hawaii where I'm based now. I started Plate Lunch Collective in March 2025 because I could see the shift to AI interfaces and retrieval-layer discovery happening and I wanted to build something specifically for it. Not retrofit an existing agency. Not bolt "AI" onto a service page and hope the market didn't notice. Build from the ground up for how search actually works now. That background is why I can write this piece. I've sat on both sides of the agency-client relationship long enough to know what the work looks like when it's real and what it looks like when it's repackaged.

The terminology you'll encounter (and what it actually means for hiring)

Before you can evaluate an agency, you need a quick handle on the vocabulary. The market hasn't standardized yet and agencies use these terms inconsistently, which is part of the problem.

AI SEO is the umbrella term. It's what most people search for. Underneath it sit three disciplines that overlap but involve different tactical work.

GEO (Generative Engine Optimization) is the work of getting your brand cited by AI platforms. ChatGPT, Perplexity, Claude, Gemini. When someone asks an AI "which accounting firms in Denver handle nonprofit audits" and your firm appears in that answer, that's GEO working. A 2024 study out of Princeton and IIT Delhi found that content is significantly more likely to be cited by AI models when it includes citations, statistics, and quotations from credible external sources, boosting visibility by up to 40%. The takeaway isn't that AI ignores brand-owned content. A separate Yext study of 6.8 million AI citations found that 86% came from brand-managed sources. The takeaway is that your content, wherever it lives, needs to demonstrate the kind of verifiable authority that AI systems look for when selecting what to cite. Which means GEO work extends beyond your domain into how your brand is referenced and validated across the web. I explored what happens when brands don't control that narrative in a piece about Nike and Darc Sport, where AI systems routed discount code queries to affiliate sites because the brands themselves hadn't structured their promotional content for retrieval.

AEO (Answer Engine Optimization) focuses on Google's AI features specifically: AI Overviews, featured snippets, People Also Ask boxes, voice results. This is where traditional SEO and AI optimization share the most DNA, but the tactics differ because you're optimizing to be extracted and cited inside a generated answer, not just ranked in a list.

Social search optimization covers YouTube, TikTok, Instagram, Pinterest, Reddit, LinkedIn as search engines, which they now are. Each has its own algorithm and its own signals for what surfaces. This isn't social media management. It's search optimization on platforms that happen to be social.

Most agencies you'll talk to are strong in one of these areas and vague about the others. Some cover two. Very few genuinely integrate all three with the traditional SEO foundation underneath. That's worth knowing before you start taking calls.

What honest claims sound like (and what should make you pause)

This is where I want to be direct, because the pitches you're going to hear from agencies in this space will vary wildly in their relationship to how these systems actually work.

Nobody controls what an AI model cites. The honest version of this work is: we improve your eligibility to be retrieved and cited. Structure, entity clarity, topical coverage, trust signals, the infrastructure that makes it more likely these systems select you. That's real, valuable, technical work. But it's probabilistic. Any agency that talks about it like they've cracked a code or found a lever is selling certainty the systems don't offer.

AI Overviews are still running searches. Google's own documentation describes a technique called "query fan-out" that its AI features use: the system issues multiple related searches across subtopics and data sources, retrieves pages from the web, and synthesizes those results into a response with supporting links. Google Search Central states explicitly that this is designed to show "a wider and more diverse set of helpful links than classic search." So when an agency implies that AI has disconnected from the search engine entirely, that citations come from some black box only they understand, they're contradicting what Google has documented about its own systems. The AI runs searches. It retrieves pages. It surfaces links. The foundational work of being retrievable and well-structured still matters. It just matters across more surfaces.

E-E-A-T is not a ranking lever. You'll hear about it in almost every agency pitch. E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness, and it comes from Google's Search Quality Rater Guidelines. It's a useful framework for thinking about content quality. But Google's Search Liaison has stated that their systems "aren't looking for E-A-T" as a direct signal, and that rater feedback isn't used directly in ranking systems. It's used to evaluate whether changes to those systems improve results overall. So when a vendor tells you they'll "optimize your E-E-A-T score" and that it directly improves your rankings or citations, they're selling marketing shorthand for something more nuanced than they're letting on. Aligning with E-E-A-T principles is smart. Treating it as a switch you flip is a misunderstanding of what Google has said about its own infrastructure.

The framing I'd trust sounds something like: we improve your eligibility to be retrieved and cited by making your content more structured, your brand entity more clear, your topical authority more comprehensive, and your trust signals more consistent across the platforms where AI systems look for sources. We test and measure citation patterns because the systems vary by query and feature. We align with quality frameworks because they reflect what these systems tend to reward, even if the relationship isn't as direct as a ranking factor.

Less exciting than "we'll get you cited by ChatGPT in 30 days." Closer to how it actually works.

What the work looks like compared to traditional SEO

The deliverables genuinely changed. This matters when you're evaluating proposals because it's the clearest way to tell whether an agency has retooled or relabeled.

The content approach line surprises most people. Citation architecture requires covering entire topic areas at a depth that keyword targeting never demanded. Some agencies express this as raw volume, producing 20, 40, 60 articles a month. Others focus on structural depth, entity coverage, and schema work that makes a smaller body of content more retrievable. The right approach depends on the vertical, the competitive landscape, and how much foundational work already exists. But the scale and intent of the content is fundamentally different from writing blog posts to rank for phrases. You're building a knowledge base that AI systems can retrieve from.

The authority building line is the other one that separates real AI SEO work from a relabel. I watched a SaaS company with a Domain Authority of 71 and 18,000 backlinks get cited in only 11% of relevant AI searches. Their competitors with lower DA and fewer backlinks were getting cited more often. The difference was Reddit. The competitors had genuine presence in the forums where their buyers did research, and AI models were weighting that independent validation more heavily than traditional link authority. That's the world we're in now. Who speaks for your brand when the AI goes looking for sources isn't a theoretical question.

What AI SEO agencies charge in 2026

The market is young enough that pricing varies widely, but enough agencies have published rates or disclosed them in buyer's guides that a realistic picture exists.

Agencies that have made their pricing public:

The important caveat with every number on this page: most of these agencies price for one or two of the disciplines I described above. A GEO shop may not touch social search. An AEO specialist may not do entity work across platforms beyond Google. Finding an agency that genuinely integrates GEO, AEO, social search optimization, and the traditional SEO foundation underneath into a single strategy is still uncommon in this market. Which means the real cost calculation often involves either stacking multiple specialists or finding the rare shop that does the integration work.

How to evaluate who you're hiring

A few things I'd listen for in conversations with agencies, based on patterns I've seen over twenty years of doing this work across different markets and verticals.

Can they name the specific platforms and explain how the work differs for each one? ChatGPT citation works differently than Perplexity retrieval, which works differently than Google AI Overviews, which works differently than Reddit search or TikTok search. If the conversation stays at the level of "AI search" as a single thing, the work probably stays at that level too.

How do they describe the mechanics? Do they explain AI search as systems that retrieve and synthesize information from the web, consistent with what Google has documented about query fan-out? Or do they imply some proprietary understanding of a black box that only they can crack? The agencies worth hiring are the ones whose explanations align with the primary sources.

What do they measure? Gartner predicted that traditional search volume would drop 25% by 2026 as users move to AI platforms. If an agency still measures success primarily through keyword rankings and Google organic traffic, they're reporting on a shrinking slice of how discovery actually works. Citation rate, AI share of voice, platform-specific visibility, attributed pipeline. Those are the metrics that map to the current landscape.

Ask them about E-E-A-T directly. If they tell you they'll optimize your E-E-A-T score as a ranking lever, ask them what Google's Search Liaison has said about how E-E-A-T relates to ranking systems. The answer will tell you whether they've done the reading or whether they're repeating conference slides.

What's their third-party authority strategy? AI models cite independent sources more readily than brand-owned content. If the entire strategy lives on your website, they're missing the mechanism that drives AI citation. Reddit, review sites, digital PR, professional forums. These aren't add-ons. They're where AI systems look first.

Do they understand that the work compounds? The retrieval layer isn't a campaign you run. The signals you build today inform the models that answer tomorrow's queries. Brands that are citable now become more citable over time as the systems learn to weight them. Work structured in focused sprint blocks, where each period builds on the last, tends to produce better results than open-ended retainers where deliverables drift. If three months of work doesn't create a foundation that six months builds on, something is wrong with the approach.

What realistic budgets look like

The table above shows what individual agencies charge for their piece of the work. These numbers reflect what it actually costs when you account for the scope most businesses need, which often spans multiple disciplines that a single agency may not cover.

For a small business that needs foundational work and strategic direction: $2,000 to $5,000 per month gets you started with either consulting and partial execution or a productized service at the lower tier.

For a mid-market company that needs full execution across GEO, AEO, and social search: $8,000 to $20,000 per month. The combination of content architecture, technical implementation, entity optimization, and cross-platform authority building drives a significant portion of that cost.

For enterprise with complex needs, multiple product lines, or international operations: $20,000 to $50,000+ per month.

These numbers will shift as the market matures. More agencies will enter. Tooling will commoditize some of the work. Pricing will standardize. But right now, the premium reflects genuine scarcity of expertise and the complexity of integrating multiple disciplines into something coherent.

The compounding question

The businesses I've watched win these kinds of inflection points, the shift to mobile, the arrival of local search, the first algorithm updates that wiped out entire business models, were the ones that moved before the market settled. Not because they had better information than everyone else but because they were building authority while their competitors were still debating whether the shift was real.

AI systems compound. The signals you send today, the structured data, the entity clarity, the topical depth, the independent validation, all of it feeds the models that generate tomorrow's answers. And the competition for citation is fierce. ChatGPT typically cites between 3 and 8 sources per answer. Perplexity can cite upward of 20. Google AI Overviews average around 13. The window for visibility in any given answer is narrow, and the brands that are citable now are building on ground that gets harder and more expensive to claim the longer you wait.

I've laid out the numbers. The cost of the work is real. The cost of arriving after the positions are established is the one nobody puts in a proposal, but anyone who's ever tried to build authority against an entrenched competitor knows the math.