Sean Walsh
Sean is a Director at Intelligency heading up our digital marketing and client services operations. Sean has 15+ years experiencing working both in-house and agency with brands including Lloyds, Alstom, Hitachi, Lufthansa, Viaplay, DFDS Seaways and Mercedes-Benz.
Agentic Engine Optimisation, or AEO, has become one of the more discussed topics in digital marketing in 2026. The coverage has generated a fair amount of heat but not always much light, partly because the tooling landscape is still developing and partly because a lot of what is being written treats AEO as something entirely new when, in practice, it shares most of its foundations with work that good SEO practitioners have been doing for years.
This article covers the tools that are actually useful right now, split into those with a clear proven use case and those worth testing as the category matures. But before getting into the tools, it is worth addressing the terminology question directly, because the shift in how AI systems retrieve and surface content has caused some confusion about what has actually changed and what has not.
AEO and SEO: different names, same foundation
Despite what some of the more excitable coverage suggests, AEO is not a replacement for SEO, and it does not require a completely different strategic approach. The two disciplines share the same core premise: make your content easy to find, easy to understand, and clearly relevant to what someone is trying to know or do.
The difference is in the audience being optimised for. Traditional SEO focuses on helping human searchers find and engage with your content. AEO extends that to cover AI systems that fetch, parse and use your content to formulate answers, often without a human ever clicking through to your site. The signals that matter are largely the same: well-structured pages, clear headings, specific and accurate information, strong authority and credible backlinks. What changes is the layer of intent you apply when thinking about how that content is read and used.
Research consistently shows that AI Overviews and similar systems draw heavily from pages that already rank well organically. Google has been clear for some time that content quality and audience relevance are the primary factors that determine whether a site performs. AEO does not change that message. It adds a layer of consideration: once your content is authoritative and well-structured, is it also legible and extractable for AI systems working within processing constraints?
In practical terms, we treat AEO and SEO as the same discipline. The same improvements that help AI systems cite your pages accurately also make those pages clearer and more useful for human readers. They are not in tension. The tools below reflect that: some are well-established SEO tools that remain highly relevant in an AEO context, and some are newer platforms built specifically to measure AI search visibility.
The tools with a clear, proven use case
1. LLM assistants used with a defined methodology
ChatGPT, Claude and Gemini are themselves useful AEO research tools when used intentionally rather than ad hoc. The most practical applications are competitive landscape research, content gap analysis, prompt testing to understand how AI platforms respond to queries in your category, and entity and topical coverage audits.
Asking an LLM what it knows about your brand, your competitors and your sector, and then interrogating where the gaps and inaccuracies are, is a fast and accessible way to understand your current AI search position. Most businesses have not done this basic audit, and a meaningful first pass takes less than an hour. It is also one of the few AEO-relevant activities that costs nothing beyond the time invested.
2. Google Search Console
Search Console remains one of the most important tools in any AEO workflow, primarily because it provides direct performance data from Google: the platform that produces the AI Overviews appearing above organic results for a significant proportion of searches. Understanding which of your pages are currently being surfaced in AI Overviews, and which are not, gives you a baseline from which to measure the impact of content changes.
It also helps identify the queries where AI Overviews are appearing for keywords you rank for, which is increasingly important as AI-generated answers above the fold reduce click-through rates on the organic listings below them. Knowing where you are losing clicks to AI answers on your own target keywords is the starting point for deciding where to focus content improvement efforts.
3. Google Trends
Google Trends serves a different purpose than Search Console, but it is equally valuable for AEO strategy. Where Search Console tells you how you are performing, Google Trends tells you where demand is heading. It does not give absolute search volume, but it gives relative momentum across topics and queries, which is often more strategically useful when trying to get ahead of emerging patterns rather than simply responding to existing ones.
For AEO specifically, rising query trends can signal emerging answer opportunities you can address before your competitors do. AI systems tend to favour content that is well-established and authoritative on a topic, which means the window for getting in early is narrow. Identifying rising demand trends through Google Trends and creating strong content quickly is one of the more practical ways to build AI citation presence in a new area before it becomes competitive.
4. SE Ranking and SE Visible
SE Ranking is the platform we use day-to-day for client SEO work, and its relevance to AEO has grown considerably over the past 12 months. The AI Overviews Tracker monitors how your keywords are performing within Google’s AI-generated results, including citation frequency, source analysis, and estimated traffic impact from AI Overviews. It also identifies which competitor domains are being cited in AI answers for keywords you are targeting, which is actionable competitive intelligence.
The AI Search Toolkit extends this further by tracking brand mentions and linked citations across AI Overviews, AI Mode, ChatGPT, Gemini and Perplexity. You can monitor how often your domain is cited, whether citations are linked or unlinked, and how this compares to named competitors over time.
SE Visible is a companion product that sits alongside SE Ranking and focuses specifically on brand AI visibility at a strategic level: how your brand is presented, ranked and perceived across AI systems. It provides a Brand Visibility Index that measures performance over time and competitive benchmarking across AI platforms. For agencies managing multiple client accounts, the combination of SE Ranking for tactical execution and SE Visible for strategic oversight is a coherent and cost-effective approach.
5. Semrush
Semrush has expanded its feature set to include AI Overviews tracking and visibility data, making it one of the more complete tools for monitoring how content performs across both traditional search and AI-generated results within a single platform. For teams already using Semrush for keyword research, position tracking and site auditing, the AI visibility layer adds meaningful value without requiring a separate tool or workflow.
The topic clustering and content gap analysis features are particularly relevant for AEO, helping identify where topical coverage is thin relative to what AI systems are pulling from competitors. Thin or fragmented coverage in a topic area is one of the more common reasons a site gets passed over in AI-generated answers in favour of a competitor with more comprehensive, well-organised content on the same subject.
6. Profound
Profound is purpose-built for AI search monitoring. It tracks how platforms, including ChatGPT, Perplexity, Google AI Overviews, and Claude discover, surface and cite your brand and content. It monitors brand mention frequency and sentiment, competitor share of voice, and the specific prompts that trigger your content to appear in AI-generated answers.
The most useful shift Profound enables is in the metric itself. Rather than asking where you rank in a search result, you can ask: when AI answers a question in your category, are you in the answer? The cross-platform view, covering multiple AI engines simultaneously rather than one in isolation, is its most distinctive feature and makes competitive benchmarking significantly more meaningful than single-platform tracking.
It is not a cheap tool and is better suited to businesses with an existing content and SEO foundation. For agencies managing multiple clients in competitive sectors, the monitoring and benchmarking functionality is particularly valuable.
7. Screaming Frog
Screaming Frog has been a technical SEO staple for years, and its relevance extends directly into AEO. Many of the technical issues that prevent AI agents from correctly parsing and using your content are exactly the issues Screaming Frog identifies: missing or misconfigured structured data, poorly structured heading hierarchies, thin or duplicated page content, and slow server response times.
Running a Screaming Frog audit with a focus on schema markup completeness, heading structure, and page-level content depth is one of the most practical first steps in any AEO improvement programme. The tool now integrates with Google Search Console and PageSpeed Insights, making it straightforward to cross-reference technical findings with actual performance data.
8. Google Rich Results Test and Schema Markup Validator
Structured data is one of the cleaner signals available for AI retrieval. Schema markup for FAQs, services, reviews, products and local business information gives AI systems a reliable, machine-readable layer of data to draw from, independent of how the surrounding content is written or formatted. Getting this right is a relatively contained piece of work that can have a disproportionate impact on how accurately your content is cited.
Both tools are free. The Rich Results Test checks whether your structured data is correctly implemented and eligible for enhanced display in search results. The Schema Markup Validator checks for errors and warnings at a more granular level. For businesses in sectors where FAQ, review or service schema are applicable, a structured data audit is one of the most immediately actionable AEO improvements available.
How to approach this practically
The AEO tools market has grown faster than the evidence base for what actually works. Many platforms are repackaging existing SEO or content analytics functionality under AEO branding without meaningfully changing what they measure. The most reliable signal for whether a tool is genuinely useful is whether it changes a specific decision you make about your content or your site.
A practical starting sequence looks like this. Use an LLM to audit your current brand position across AI platforms in your category. Use Google Search Console to understand which of your pages are appearing in AI Overviews and where the gaps are. Use Google Trends to identify rising demand patterns worth targeting early. Use Screaming Frog and the schema validation tools to fix any technical issues preventing your content from being correctly parsed. Then use SE Ranking, Semrush or Profound, depending on the depth of monitoring your situation requires, to track how your visibility is changing over time.
Starting with the fundamentals, well-structured content, strong authority signals, accurate structured data, and a clear technical foundation will deliver more impact sooner than any monitoring platform can on its own. The monitoring tools tell you whether the work is making a difference. They are not a substitute for doing the work.
