Who owns AEO? Three surveys give three different answers

Ask an SEO professional who should own Answer Engine Optimisation and the answer may sound straightforward: SEO.

Ask a broader marketing organisation and the picture becomes considerably messier.

A 2025 BrightEdge survey of more than 750 search, content and digital marketing professionals found that 54% of organisations relied on SEO or Digital Marketing to lead AI-search efforts. Content or Editorial followed at 14%.[1]

A 2026 Semrush survey retained 481 responses from marketers, SEO professionals and business owners working with organic growth. No function reached 20%. A dedicated AEO or GEO specialist or team led at 18%, followed by SEO at 16%, Content at 15% and shared ownership at 14%. One in ten respondents reported no clear owner.[2]

Then an August 2026 Sword and the Script survey of 200 U.S. marketing and communications professionals produced a third answer. Marketing Operations led at 17%, followed by Product Marketing at 14%, Social Media at 13% and Creative or Design at 13%. SEO or Organic Search received 8% and PR or Communications 3%.[3]

That is not a consensus. It is barely a pattern.

The easy conclusion is that marketers have not decided what AEO is. A more useful interpretation is that each discipline sees the part of AEO it already knows how to solve. SEO sees retrieval. Content sees information. PR sees authority. Brand sees positioning. Product Marketing sees claims. Social sees conversation. Customer Insights sees demand. Marketing Operations sees measurement.

They are all partly right.

The governance problem is not that AEO has no natural home. It is that no single marketing discipline controls all the inputs that determine how an AI system represents a brand.

<blockquote>AEO needs one accountable owner. Good AEO cannot be done by one discipline alone.</blockquote>

<h2>The surveys are not directly comparable</h2>

The ownership percentages should not be pooled or treated as competing estimates of one universal reporting structure.

BrightEdge surveyed search, content and digital marketing professionals. Its finding that SEO or Digital Marketing led in 54% of organisations makes sense within that frame, but it should not be generalised to every corporate function.[1]

Semrush sampled people working with organic growth. Its wider role mix produced a more fragmented result, but the sample still sits close to search and content practice.[2]

Sword and the Script surveyed U.S. marketing and communications professionals through a commercial panel. Seventy-six per cent worked in-house, but the sample contained only 200 respondents and measured their perceptions of responsibility, not which operating model objectively produces the best results.[3]

The disagreement is nevertheless informative. Where somebody sits influences what that person thinks AEO is. That may be the organisational problem hiding underneath the acronym.

<h2>SEO has a legitimate claim</h2>

SEO is essential to AEO. AI systems cannot use web information they cannot find, access or interpret.

Technical SEO contributes crawlability, indexation, information architecture, structured data, entity clarity, query analysis and machine accessibility. Product truth that is buried, contradictory or poorly structured is not especially useful to an answer engine.

Semrush also found that 77% of respondents put AI search somewhere inside the SEO tent: 55% described it as an extension of SEO and 22% as partially overlapping. Only 15% considered it an entirely separate channel.[2]

The argument is not that AEO should be taken away from SEO. It is that technical discoverability is only one determinant of what an AI system ultimately says about a brand. As AEO Updates has argued in <a href="/articles/seo-is-not-aeo">SEO is not AEO</a>, the corporate website is part of the evidence environment, not the whole of it.

Consider a customer asking which family SUV is safest. SEO can help ensure that a manufacturer’s safety information is retrievable. It does not decide what the brand should stand for, whether safety matters to the target customer, which claims are defensible, whether independent tests support them, what automotive journalists report, what owners experience or whether the product performs as promised.

Those inputs belong to different disciplines.

<h2>AEO does not merely optimise a webpage. It influences a conclusion</h2>

Traditional search encouraged an organisational model built around earning visibility for pages. AI-mediated discovery creates a broader outcome.

When somebody asks an AI system a commercially important question, does it understand the brand accurately? Does it associate the organisation with the things it wants to own? Does it consider the brand when relevant and recommend it when appropriate?

An independent 2026 study comparing Google Search with four generative-AI systems found low domain overlap and material differences in source composition. Its source-typology analysis also found that the mix of brand, earned and social sources changed with query intent.[4]

That does not mean every AI answer follows one stable sourcing rule. It supports a narrower point: AI representation can be assembled from a different information environment from conventional search, and the useful source mix can change with the question.

A product specification on the corporate website, an analyst evaluation, an employee’s LinkedIn post, a customer’s Reddit discussion and a YouTube demonstration can all contribute evidence. The <a href="/articles/ai-citation-benchmarks-evidence-functions">AEO Evidence Map</a> treats those evidence functions as a working hypothesis rather than a settled taxonomy of retrieval behaviour.

Once the problem is framed this way, the organisational question changes. The issue is not simply who should do AEO. The issue is who owns the outcome, who diagnoses the problem and which specialist controls the lever required to change it.

<h2>The capabilities mature AEO may need</h2>

A mature AEO programme may need access to at least ten core capabilities. This is a planning model, not a claim that every organisation needs ten people in every meeting.

<table><thead><tr><th>Capability</th><th>Core AEO contribution</th></tr></thead><tbody><tr><td><strong>Brand Strategy</strong></td><td>Defines desired positioning, associations and strategic territory</td></tr><tr><td><strong>Customer Insights</strong></td><td>Identifies consequential decisions, questions and credibility criteria</td></tr><tr><td><strong>Product Marketing</strong></td><td>Establishes product truth, differentiation and defensible claims</td></tr><tr><td><strong>SEO</strong></td><td>Makes relevant information discoverable and machine-accessible</td></tr><tr><td><strong>Content</strong></td><td>Turns organisational knowledge into explicit, useful information</td></tr><tr><td><strong>PR and Communications</strong></td><td>Builds legitimate independent corroboration and authority</td></tr><tr><td><strong>Social and Community</strong></td><td>Observes and participates in human discussion and experience</td></tr><tr><td><strong>Subject-matter experts</strong></td><td>Supply identifiable expertise that Marketing cannot manufacture</td></tr><tr><td><strong>Data, Analytics and Marketing Operations</strong></td><td>Measures representation, visibility, evidence and outcomes</td></tr><tr><td><strong>Web, Engineering and IT</strong></td><td>Implements technical changes to sites, feeds, APIs and knowledge architecture</td></tr></tbody></table>

Sales, Customer Success, Product, Legal or Regulatory and Executive Leadership may also need to participate when the diagnosed problem reaches their domain.

The organisational implication of the recent <a href="/articles/youtube-linkedin-reddit-human-evidence-ai-citations">YouTube, LinkedIn and Reddit citation research</a> is not that every brand should post everywhere. Those platforms can contain different forms of human evidence. The people who understand expertise, customer experience and community discussion therefore become part of the information system AEO needs to observe.

<h2>Sometimes the correct AEO intervention is to fix the product</h2>

Imagine an AI system repeatedly says that customers like a platform’s functionality but find implementation difficult.

The AEO owner investigates and finds recurring complaints across review sites, Reddit and YouTube. Publishing 15 articles claiming the platform is easy to implement would be the wrong intervention. The AI system may be describing customer reality accurately.

The correct response could involve Product, Implementation, Customer Success and Operations. Improve the experience. Then allow the evidence environment to change because reality changed.

Good AEO should not make an AI system say something more favourable than the evidence supports. It should help the system reach an accurate, well-evidenced understanding of the brand and identify when the underlying product or experience needs to change.

That distinction is why AEO becomes bigger than content optimisation.

<h2>So who actually owns it?</h2>

AEO Updates’ proposed answer is that <strong>Marketing should own the outcome</strong>, with one named leader accountable for the organisation’s representation in AI-mediated customer decisions.

This is an editorial governance recommendation, not a result proved by the surveys. It rests on the nature of the questions AEO ultimately addresses: Is the brand present in important decisions? How is it represented? What is it associated with? Are its claims understood and supported? Does it enter consideration? Is it recommended when appropriate?

Those are questions of positioning, customer understanding, demand and choice. They belong at the Marketing level even when the intervention belongs elsewhere.

The accountable owner might lead AEO, AI Search Intelligence, Organic Visibility, Brand Intelligence or another function. The title matters less than the mandate and authority.

<h2>Shared input is necessary. Shared accountability is dangerous</h2>

If SEO, Content, PR, Brand and Social all own AEO, nobody may own the outcome.

Semrush found that only 22% of respondents had fully integrated SEO and AI-search execution across strategy, execution and reporting. Among respondents reporting AI-related results, 27% had fully integrated execution compared with 12% of those not reporting results. Only 3% of teams reporting results said they had no clear AI-visibility owner, compared with 22% among teams not reporting results.[2]

Semrush also reported that 81% of teams with fully integrated execution saw more traffic or leads connected to AI platforms, compared with 36% of teams running the work separately.[2]

These associations are directionally useful but not causal proof. Successful or better-resourced teams may be more likely to formalise ownership, buy tools and integrate workflows. The study is self-reported and Semrush uses the analysis to promote its products.

The evidence supports investigation, not a universal org chart.

The useful distinction is between shared input and shared accountability. The first is necessary. The second creates diffusion.

<h2>A better operating model: broad inputs, narrow accountability, distributed execution</h2>

The proposed model has one accountable AEO or AI Search Intelligence owner responsible for a clear outcome: how is the organisation represented in AI-mediated customer decisions, why is it represented that way and what needs to change?

That central function owns the intelligence and orchestration. Specialist teams retain control of the levers they understand.

The operating principle is simple:

<blockquote>Broad inputs. Narrow accountability. Distributed execution.</blockquote>

This can involve 12 to 15 capabilities across a sophisticated organisation. It should not become a 15-person AEO committee.

The owner’s job is not to absorb SEO, Brand, PR, Content, Research, Social, Analytics and Product Marketing. It is to run a disciplined diagnostic loop:

<ol><li><strong>Observe:</strong> What is the AI system currently saying?</li><li><strong>Diagnose:</strong> Why is it saying it?</li><li><strong>Prioritise:</strong> Which representation problems matter?</li><li><strong>Assign:</strong> Which organisational capability controls the relevant lever?</li><li><strong>Intervene:</strong> The specialist function makes the change.</li><li><strong>Measure:</strong> Did the representation or business outcome change?</li><li><strong>Learn:</strong> What does the result reveal about the brand, evidence environment and customer decision?</li></ol>

<aside class="not-prose my-10 border border-[#A66A12] bg-[#F6F1E7] px-5 py-6 sm:px-8 sm:py-7" aria-labelledby="aeo-governance-worksheet-title"><p class="mb-2 font-mono text-[11px] font-semibold uppercase tracking-[0.16em] text-[#A66A12]">Practical worksheet</p><h3 id="aeo-governance-worksheet-title" class="mb-3 font-serif text-2xl font-semibold leading-tight text-[#241A10] sm:text-3xl">Put the AEO operating model to work</h3><p class="mb-5 max-w-2xl text-[15px] leading-7 text-[#51493F]">Use this six-page, 45 to 60 minute working session to name one accountable owner, choose priority AI-mediated customer decisions, map evidence gaps, assign specialist interventions and establish a 30/60/90-day operating cadence.</p><a href="/manus-storage/aeo-governance-worksheet_60c34715.pdf" target="_blank" rel="noopener noreferrer" download="AEO-Governance-Worksheet.pdf" class="inline-flex min-h-11 items-center justify-center bg-[#241A10] px-5 py-3 font-mono text-xs font-semibold uppercase tracking-[0.12em] text-[#F6F1E7] no-underline transition-colors hover:bg-[#A66A12] focus-visible:outline focus-visible:outline-2 focus-visible:outline-offset-2 focus-visible:outline-[#A66A12]" aria-label="Download the AEO Governance Worksheet PDF, six pages">Download the worksheet PDF <span class="ml-2" aria-hidden="true">↓</span></a><p class="mt-3 text-xs text-[#6E665C]">Six printable US Letter pages. No sign-up required.</p></aside>

The central function owns Observe, Diagnose, Prioritise, Assign, Measure and Learn. Specialist teams largely own Intervene.

That is a different organisational model from building another channel team. It also reinforces why AEO measurement needs an explicit methodology. The <a href="/articles/behind-aeo-dashboard-ai-search-measurement">AEO dashboard measurement framework</a> separates prompt design, observation, evidence records and calculations so the owner can distinguish a real representation problem from a measurement artefact.

<h2>Three problems, three different owners of the intervention</h2>

If an AI system incorrectly says a product does not integrate with Salesforce, the investigation may find that the integration exists but is poorly documented. Product Marketing, Content and SEO or Web control the intervention.

If the AI system understands the features but does not consider the brand among the safest products in its category, the evidence gap may be independent substantiation. Brand, Product, Research and PR or Communications control that intervention.

If the AI system repeatedly says customers find a service difficult to use and the customer evidence supports that conclusion, Product and Customer Success control the intervention. The answer is not more AI-optimised content. The answer is to fix the problem.

Assigning AEO entirely to whichever department first purchased an AI-visibility platform risks solving the wrong problem.

<h2>The surveys disagree because AEO runs horizontally</h2>

SEO professionals see machine retrieval, search behaviour and discoverability. Product marketers see product claims, differentiation and competitive representation. Social teams see human discussion and community evidence. Marketing Operations sees measurement and workflow. PR sees independent authority. Brand sees positioning.

Each view captures a real part of the system.

The disagreement may be evidence that AEO is not another marketing channel. It is an intelligence and orchestration problem running horizontally across a vertically organised marketing department.

Companies divide work by discipline. An answer engine does not respect those boundaries. It can synthesize a product specification, analyst evaluation, journalist article, executive LinkedIn post, YouTube demonstration, Reddit complaint, retailer price and competitor comparison page into one answer.

Inside the company, those inputs may belong to eight different teams. To the machine, they are evidence.

That is the structural problem AEO governance needs to solve.

<h2>AEO Updates Takeaway</h2>

AEO sounds technical because its vocabulary includes prompts, models, citations, retrieval, schemas and crawlers. The hardest questions are more familiar: Who is the customer? What matters to that person? What should the brand stand for? What can it credibly claim? Why should anybody believe it? What does the customer actually experience?

AI has created a new intermediary between the customer and the evidence. It has not removed the need for Marketing to answer those questions.

The better ownership test is not whether the org chart says SEO, Content, Product Marketing or AEO. It is whether one person has explicit accountability for how the brand appears across AI-mediated customer decisions and enough authority to diagnose problems and mobilise the specialist functions capable of fixing them.

Without that, the organisation does not yet have an AEO operating model. It has a collection of AEO activities.

One owner cannot create customer understanding, positioning, claims, evidence, machine representation, consideration and business outcomes alone. Somebody still needs to own whether those parts work together.

<h3>Sources and methodology</h3>

BrightEdge surveyed more than 750 search, content and digital marketing professionals in June 2025. Semrush retained 481 responses from more than 570 marketers, SEO professionals and business owners after an attention check; the public article does not disclose the field period. Sword and the Script surveyed 200 U.S. marketing and communications professionals through a commercial panel in July 2026. These are different samples and should not be pooled.

BrightEdge and Semrush sell SEO and AI-search products. Sword and the Script published its own survey and analysis. Meltwater’s LinkedIn citation research was conducted with LinkedIn and promotes GenAI Lens. AEO Updates has no stated affiliation with these organisations and separates their observations from its own governance recommendations.

<h3>References</h3>

[1] <a href="https://www.brightedge.com/news/press-releases/brightedge-survey-reveals-68-marketers-are-embracing-ai-search-shift" target="_blank" rel="noopener noreferrer">BrightEdge Survey Reveals 68% of Marketers Are Embracing AI Search Shift As Organizations Look to SEO Teams to Lead</a>.

[2] <a href="https://www.semrush.com/blog/the-operational-gap-ai-seo-study/" target="_blank" rel="noopener noreferrer">Only 22% of marketers have fully integrated AI search and SEO. They’re pulling ahead.</a>.

[3] <a href="https://www.swordandthescript.com/2026/08/ai-visibility-survey/" target="_blank" rel="noopener noreferrer">Survey: Marketing and comms see AI visibility as significant but are still navigating how to improve it</a>.

[4] <a href="https://arxiv.org/html/2601.16858v2" target="_blank" rel="noopener noreferrer">Navigating the Shift: A Comparative Analysis of Web Search and Generative AI Response Generation</a>.

[5] <a href="https://www.meltwater.com/en/blog/linkedin-ai-visibility-study" target="_blank" rel="noopener noreferrer">9.5M AI citations analyzed: How LinkedIn content wins AI search</a>.