How to Conduct a Technical SEO and AI Search Audit

A technical audit is an opportunity to investigate how your website works for all of your website’s different users. That includes human users, human users assisted by AI tools, search bots, AI training bots, AI interaction bots, and AI agents. 

A technical audit for SEO and AI search examines multiple factors to identify the technical issues that prevent all of your website’s visitors from correctly using the website. That includes evaluating things like:

• how the website is structured, including navigation and internal links
• if the website’s code correctly supports the website’s content
• how the pages load, including speed, rendering, and hidden content reviews
• how the server is configured and if any blocks or restrictions are in place
• if technical errors will prevent bots, agents, or humans from accessing content

If search bots cannot correctly use your website, your website will not rank. If AI training bots cannot correctly use your website, your website will not be included in training data, which can limit mentions. If AI agents or human visitors cannot correctly use your website, then you will lose conversions. An audit is an opportunity to find the technical issues affecting all the automated and human visitors that are accessing your website.

In this article, I’ll walk through how to approach a technical audit to improve SEO and AI search performance. I’ll also walk through the mistakes I’ve seen clients make when conducting audits.

Two Common Audit Mistakes

A Technical Audit Is an Exploration, Not a Checklist

Let’s start with the biggest mistake I see clients make: relying too heavily on tools during an audit. Many SEO tools offer this type of audit. For example, Screaming Frog, Ahrefs, Semrush or others will scan your website and report on a list of issues found. Lately I’ve seen clients do something similar with AI tools.

These types of site scans run through a checklist of issues. They can tell you if your website is passing Core Web Vitals, if your website has broken links or duplicate content, if it is missing title or canonical tags, if there is invalid alt text or invalid schema, and so on. As part of the audit, the tool may also tell you some of the things that you need to fix. AI tools can also give you more specifics on how to fix the issues found.

While using a tool like this to run through the checklist is useful to identify basic issues, checklist-style audits are only the starting point. They tell you that something exists but not why it exists, whether it matters, what actually should be done about it, or how it fits into the broader context of your marketing strategy and business goals.

The site scans might also provide recommendations. But this is limited as well. I’ve seen too many clients identify a number of issues with these tools, invest in the fixes and get no results. I’ve also seen clients use these tools and then face uncertainty about which of those issues actually matter and what to do about them. Especially when using AI for site audits, I’ve seen a lot of false claims made by the AI system that send dev teams down the wrong path, wasting time and money.

Even if everything from the tools is accurate, there is still nuance missing. For example, a website with 10,000 404 errors may have a serious crawl waste problem. Or those 404s may be old URLs that no longer matter. A website with duplicate title tags may have a sitewide template issue. Or those duplicate titles may appear on pages that should not be indexed anyway. A website may have thousands of URLs crawled by Google, but only a small number actually earning traffic. That may point to thin content, duplicate content, poor internal linking, excessive parameters, hacked content or a mismatch between what the site publishes and what people search for.

Scanning tools and AI assessments may not fully appreciate the technical nuances involved. During an audit, I have often seen the same issue affect different systems in different ways. A JavaScript rendering problem may prevent AI crawlers from seeing important content but not be a problem at all for Google. A confusing URL structure may cause Google to ignore canonical tags, but OpenAI doesn’t appear to use canonical tags (or at least hasn’t publicly confirmed this). An overly restrictive robots.txt file may block AI search bots from accessing content that you actually want included in AI responses. A form that works fine for a human visitor may be confusing for an AI agent trying to complete a task.

So, what do you need to do instead? The most important step when conducting a technical audit is to go beyond what these tools offer. Instead of treating an audit like a checklist, treat an audit like an exploration of your website. After running a scan or having AI assess your website, the real work begins with asking questions to help explore and understand the issues identified. Let’s dig into what those core questions are to explore.

Audits Should Have Unique Recommendations

Each audit is unique because each website is unique. I have found the same problem countless times on multiple websites. However, what that problem means differs depending on the nature of that website and the company’s goals. If you treat each website the same, the audit won’t do much to help.

To find what makes a website unique, you need to start an audit by understanding who uses that website and what those users need to do on the website. In 2026, website users include a mix of human and automated visitors. You have to understand two things about all of the visitors on a website:

1. Requirements. Each user is going to have a different set of requirements for what they are expecting to do on your website. A human visitor is on your website to engage with your content and convert. A search engine bot is on your website to grab content for their index. An AI agent is on your website to complete some task on behalf of a person. 
2. Capabilities. Each user is going to have a different set of capabilities. For example, a human visitor in a regular browser will be able to execute JavaScript and can likely see the bulk of the website’s content. However, if that human visitor is visiting with a slower internet connection or has an older device, they may have speed-related issues that cause problems displaying the page. As another example, an AI agent may be confused by the site’s current HTML structure and unable to find the pages it needs to complete a task.

You also need to understand what your expectations are for each type of visitor to the website. Consider things like:

• What pages do you expect Google (and other search engines) to index and return in rankings?
• Which content, if any, do you want AI training crawlers to access? 
• Which pages should AI search crawlers be able to retrieve and cite?
• What are the ways you expect users to engage and convert?
• What pages do AI agents need to find? What forms do agents need to use?

An audit needs to find and prioritize the problems at the intersection of what users want and the company’s expectations. An AI agent may be unable to complete a given task on a website, but the company may have no interest in supporting AI agents completing that task. A search engine may be unable to access some content on the website, but maybe that isn’t content they should access because it is meant for AI training or users instead.

Questions to Explore in an Audit 

1. Can the right systems access the right content?

Bots are a key part of the audience, so you want to check if the main search and AI bots can crawl your website. This includes Google’s different bots, Bingbot, and bots from other traditional search engines. It also includes AI bots from OpenAI, Anthropic, Perplexity, and others. 

In our audits, we have increasingly found sites where AI-related bots are being blocked by accident. In one audit, server logs showed that a major AI search crawler was consistently receiving 403 Forbidden responses, despite the robots.txt file containing no rule that should have triggered those errors. The block was happening at the CDN or firewall level, and the team responsible for that configuration had not been aware that these bots existed, let alone that they were being turned away.

Bot management tools, WAFs, and CDN security configurations often treat unfamiliar user agents as suspicious by default. Cloudflare has default settings that may conflict with your preferences. If the business has decided that it wants to be visible in AI search results, that intent needs to be reflected in every layer of the infrastructure that can block a request, including the server configuration and rules in the robots.txt file.

Along with bots, AI agents are also increasingly using websites on behalf of visitors. Even if bots are allowed, server rules may block AI agents from accessing the website. A study in April 2026 found that AI agents primarily use product and search pages, so check if AI agents can access your website’s search and product pages. Of course, how AI agents use your website may differ from this study, so survey your customers to see how (and if) they are using AI agents and then make sure AI agents can access the necessary parts of your website.

That same study also found that human visitors are more likely to use AI agents inside a browser, rather than standalone agents. Does your website work correctly in AI browsers or browsers with AI assistants? Speaking of human visitors, you also need to consider what types of devices visitors are using and confirm the website correctly loads across different browsers and different devices.

The goal is not to allow every bot to access every page of the website automatically or make the website work for every AI agent. Instead, you want to make intentional decisions about which pages each bot needs to see and which tasks each agent needs to complete. Different bots and agents may deserve different rules based on the company’s goals.

2. Can the content be rendered and understood?

Just because a user can access the page does not mean its content is visible. If important content is loaded only after JavaScript executes, some AI bots may not see it. Google does execute JavaScript, but this happens after the initial crawl of the website, so even they may miss content loaded by JavaScript. JavaScript can also make it harder for some AI agents to use the website and may also present challenges to visitors using assistive technologies. The audit should compare what exists in the raw HTML and what appears in the rendered page (after JavaScript executes) to clearly understand what search engines index and what AI systems appear able to retrieve.

Rendering issues appear across a large number of sites. In one audit of a site with hundreds of location pages, we found that title tags, canonical tags, and meta descriptions were all loaded via JavaScript rather than included in the server-side HTML. The rest of the site content was loaded without JavaScript. The result was intermittent rendering: sometimes Google picked up the correct canonical and indexed the page correctly, and sometimes it did not. That inconsistency contributed to a significant portion of location pages dropping out of the index over several months, despite the pages working correctly for human visitors to the website.

On another site, key product content, pricing details, and images were only loaded after interacting with the page. That meant the information could not be seen until a user interacted with the page and JavaScript executed. Google does load some JavaScript, but does not interact with the page, so none of this content was visible to Google. This content was also not visible at all to AI bots, so AI bots were effectively seeing empty pages and this site was not being cited in relevant prompt responses. 

Along with JavaScript execution, there can also be problems with the website’s HTML. If the HTML lacks meaningful headings, links, labels, and structure, the page may be harder to interpret. If the content is technically present but buried inside tabs, accordions, scripts, or complex components, it may be available to one bot but unavailable to another. Semantic HTML is one solution, but it can also be implemented improperly and in ways that create even more confusion. The audit needs to step through the HTML to ensure it is correctly explaining the page and site structure.

To help bots understand the page, many sites are using schema markup within the HTML. This may be useful. However, schema can also present challenges. For example, we have found sites using review schema on pages with no visible reviews. Instead of improving understanding, that makes the page more confusing for bots. This can sometimes happen with plugins that automatically add breadcrumb schema to the page even though no breadcrumb navigation is presented to visitors. As part of an audit, you want to make sure schema supports understanding without causing confusion or discrepancies.

3. Is the website sending consistent signals?

Search and AI bots rely on signals. Some are explicit, like canonical tags, redirects, XML sitemaps, noindex tags, and HTTP status codes. Others are more implicit, like page templates, navigation patterns, content duplication, entity references, URL structure and site architecture. Human visitors rely on signals too, like page headings, internal links, and call-to-action placement. When those signals conflict, bots, agents, and human visitors have to choose what to trust. 

For example, internal links may point to one version of a URL, canonical tags point to another, redirects point to a third, and the sitemap lists a fourth. Which URL should a search bot include in the index? Google doesn’t make consistent choices here. In sites we’ve audited, we’ve seen Google trusting internal links instead of canonicals and trusting canonicals instead of internal links.

As another example, we frequently find websites with a lot of extraneous pages, like tag pages, category pages, author pages, or paginated archive pages. These pages are indexable and included in internal links, for all visitors to find. While these pages are not always a problem, they can become a form of low-quality content when they are generated automatically without being intentionally written, curated, or managed. Because they are indexable and internally linked, they also become part of the broader website Google evaluates. These types of pages can also make it harder for human visitors and AI agents to use the website.

The audit needs to identify these points of confusion where those conflicts exist and evaluate what problems these types of conflicts may be causing for different types of visitors.

4. Are the right pages being indexed, ranked, cited, and accurately summarized?

A perfectly technical website is not the goal. A page can be crawled and indexed and still earn no traffic. A page can rank but not stand out against competitors. A page can be crawled by AI systems but not cited or mentioned in generated responses. A brand can be mentioned in AI search but described inaccurately.

A modern audit needs to look beyond whether a page is technically accurate. It should ask whether the right pages are surfaced in a way that contributes to visibility in traditional search results and in AI responses. An audit should identify technical issues and opportunities that can help the website perform better in rankings and responses. 

In traditional search results, you want to review the search result ranking. Start by reviewing which pages are indexed and which pages rank for important searches. Are high-value pages indexed but missing from the rankings? That can happen when pages have insufficient internal links or structural issues. Is Google ranking the wrong page? That can sometimes happen with duplication. Are low-value pages being indexed while more important pages receive little visibility? That suggests Google is confused about the site hierarchy.

Ranking position only tells part of the story. You also need to review how each page is presented in the search results. Two of the most important components are the title link and the descriptive snippet and both should be reviewed carefully across a number of search terms and pages.

• Google rewrites title tags often, with one study from 2025 finding that 76% of title tags had been changed. How much is changed varies depending on search intent and the nature of the original title tag. In some cases, Google is rewriting the title tag because of low-quality content. However, in other cases, the title tag is being rewritten because of a structural or technical issue. We’ve seen a lot of websites using simple templates for their titles that result in poor title tag output. Adjusting the template can improve the title and reduce how much the title tag is rewritten. We’ve also seen sites where the title tag text is loaded via JavaScript. While the title text loaded by JavaScript is good, Google may not see it and then rewrite it.
• Most search result rankings extract some relevant text from the page to show as a snippet within the result. This text could be from the meta description tag, which is why it is important to include a unique, optimized meta description on each page. However, more often, the text is extracted from the other content on the page. During an audit, you want to review where the text is extracted from and see if there are technical issues or missed opportunities to help Google extract better text from the page. Changing the HTML structure may sometimes change what text appears in the ranking.

With AI search, the goal is about earning citations and being mentioned in the response itself. Rendering, page structure, and bot access all factor into being mentioned and cited. There are several tools available to help track mentions in AI responses. This can be useful to get an idea of how your company shows up in AI responses compared with your competitors. A lack of mentions relative to competitors typically means you need more content on your website, technical issues are holding back AI search performance, or that you need other people to discuss your company more. As a result, this can be useful to use during an audit to understand what problems exist. 

However, along with confirming that the website is cited and mentioned, an audit also needs to review if the mention is accurate and includes the right types of pages. In several audits, we’ve seen ChatGPT, Gemini, and Claude confidently state that a website doesn’t offer a certain product for sale, even though it does. We’ve seen AI responses state inaccurate pricing or availability. We’ve seen it provide wrong information about the company’s history or customer service policies. These types of issues can stem from conflicting information on your website, third-party websites, or from technical issues where AI systems are unable to access your website to get accurate information.

Finally, it is also important to evaluate prompt responses by asking specific questions about the company itself. You want to understand the depth, breadth, and correctness of the information included. Even if those are prompts your customers may not ever use, these types of prompts highlight what AI systems currently understand (or think they understand) about your company. It is also useful to know what pages AI systems are drawing upon to build this information. You would expect them to use the About pages on your website, but if they aren’t, check how those pages are built and linked to throughout the website. We’ve seen plenty of About pages that lack proper structure, receive very few internal links, or have rendering issues. Those problems may contribute to incomplete or inaccurate information about the company appearing in AI responses.

When testing rankings or responses, remember that search results and AI responses are highly personalized. Test from different accounts, test in logged-out states, use a VPN to test from different locations, and try variations in phrasing to make sure you are fully capturing the variety of results and responses that reflect your website’s performance.

Also, keep in mind that not everything is technical. Even when a problem is not technical, identifying that distinction prevents teams from investing in technical fixes that will not improve performance. The audit should separate these findings into technical fixes, content needs, external information or authority issues, and areas that require continued monitoring because no direct fix is evident.

5. Can real users and AI agents complete important tasks?

This is still a smaller part of most audits, but it is becoming more important.

Traditionally, search bots were sent to the website to fetch pages. Now, AI agents need to use the website to complete tasks. To extract content or complete tasks, AI agents may compare products, find pricing, submit a form, request a quote, book an appointment, or navigate a multi-step process.

A technical audit does not need to become a full AI agent usability study every time. But it should at least consider whether important content and actions are accessible, understandable, and testable. For a deeper discussion of this topic, see my article on AI agents and interaction.

How Often to Conduct an Audit

A small website that changes infrequently may only need a deeper technical audit every few years, with lighter monitoring in between. A large ecommerce site, publisher, marketplace, or enterprise site may need monthly or even weekly checks around specific issues.

Along with regular audits, there are a few other broad recommendations about when to conduct an audit:

1. Our general recommendation is that a technical audit should be conducted before any major site changes. That includes auditing a website before and after a redesign or migration to a new CMS. By auditing before a redesign or replatform, you can clearly identify what problems need to be addressed. Auditing after the change lets you find any new problems resulting from those changes. We frequently see redesigns cause traffic declines due to technical issues that could have been avoided. For more details, see my article about avoiding traffic drops during a redesign.

2. You should also conduct an in-depth audit after major traffic changes. Traffic drops are one of the most common reasons clients ask us to audit their website. Traffic drops often happen due to technical issues. We had one client who saw a drop in mobile traffic, but not desktop traffic. It turns out that a small design change broke the way the mobile site was rendered, preventing Google from indexing content from the mobile website.
   
   Traffic drops aren’t always technical. For another client, we traced a traffic decline to content that had been duplicated on third-party websites, either through formal syndication or informal copying. When a piece of content exists in nearly identical form across multiple domains, search engines have to choose which version to surface. The original publisher is not always the one that wins that evaluation.
   
3. An audit can also help you review problems with AI visibility and find new opportunities to appear in AI responses. If competitors begin appearing more often in AI responses, that could be because AI bots are having problems accessing or rendering your website. It could also be a problem with your website’s structure. 

Recap: What a Technical Audit May Examine

Final Thoughts

At Elementive, we’ve conducted hundreds of audits for websites of different sizes spanning different industries. Our audits are not an export of warnings from a scanning tool. Instead, each audit is an opportunity to identify problems affecting SEO and AI search performance for that specific website. Based on that website’s users and the company’s goals, the audit can help explain which of those problems matter the most.

In our audits, we provide evidence explaining what is happening, why it matters, which users and systems are affected, and what should be done next. Findings are prioritized based on likely impact relative to the company’s goals. However, findings also need to assess the effort required to address them, so we spend time during an audit discussing the problems with the company’s developers.

The tools used will differ based on what is found on a website. Depending on the website and the questions being investigated, the audit may incorporate crawl data, server logs, Google Search Console and analytics data, testing in different browsers, speed and performance testing, AI crawler activity, agent testing, and repeated reviews of AI responses.

For help auditing your website to improve your SEO and AI search performance, please contact me. If you prefer a more DIY approach, check out my books Tech SEO Guide and Speed Metrics Guide.