Why your marketing strategy needs an AI audit.

The way people search for information online is changing, and it’s not just about algorithms or keyword placement anymore. In 2025, artificial intelligence (AI) is reshaping search behaviour – and if marketing strategies haven’t kept pace, brands may already be falling behind. Search engines are increasingly incorporating AI-generated results and overviews, changing how brands are discovered, considered and chosen. For businesses that depend on digital visibility, it’s no longer enough to optimise for traditional search engine results pages (SERPs); you need to understand how AI systems interpret, select and present your content.

It’s a practical way to check whether your digital content is still visible in search results shaped by AI — which is why auditing your marketing strategy is no longer optional, but essential.

The AI shifts in search.

Over the past year, generative search has moved from test environments to mainstream adoption. Platforms like Google’s Search Generative Experience (SGE), Microsoft Copilot, Gemini and ChatGPT are being integrated into user search journeys. These platforms don’t just list links – they summarise, suggest and sometimes replace the need to click through. They pull from multiple sources and synthesise content into digestible answers. That means your brand’s ability to feature in AI overviews and generative snippets is now a factor in visibility, trust and traffic.

Traditional search engine optimisation (SEO) focuses on rankings and rich snippets, but generative search introduces a new layer of complexity, requiring content to be structured in a way that AI models can access, interpret, and cite. This requires rethinking how information is presented, focusing on language clarity, factual accuracy, schema markup, and page speed.

Why an AI audit is necessary.

An AI audit involves assessing how well your current marketing assets align with AI search modes and content delivery powered by machine learning models. This isn’t simply a technical exercise – it requires cross-functional insight across content, SEO, digital PR, and analytics.

Here’s what a well-structured AI audit should cover:

• Content suitability for AI citation: Is your content being referenced in AI-generated answers? If not, why? Factors such as source credibility, topical authority, factual accuracy, and clarity are crucial.
• Structured data and markup: AI systems rely heavily on structured data to identify relationships, authorship, and context. Is your content correctly marked up using schema.org or other relevant formats?
• Technical SEO health: Site speed, crawlability, mobile usability, and indexation affect whether AI can access and interpret your pages. Errors or inefficiencies here may block your visibility.
• Brand consistency and sentiment: AI summarisation tools assess language and sentiment. Poorly written or inconsistent messaging can distort how your brand is presented.
• Off-site signals and E-E-A-T: AI engines favour content that aligns with Google’s Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) framework. Are your authors properly credited? Do you have strong backlinks and brand mentions from authoritative sources?

The impact of generative search on brand visibility and strategy.

Currently, platforms like ChatGPT, Gemini and Microsoft Copilot are increasingly surfacing answers directly within the search interface, often bypassing traditional web listings. Features like Google’s AI Overviews summarise content from multiple sources into a single response panel. This means that users can get the information they need without ever clicking through to your website.

For brands, this presents a clear visibility challenge. Even if your page ranks in the top organic positions, it may be excluded from these AI-generated summaries if it doesn’t meet the selection criteria. As a result, businesses risk losing traffic, brand interactions, and conversions—not due to failing SEO, but because your content isn’t being selected by AI systems.

These platforms tend to surface content that is:

• Authored or reviewed by recognised experts

• Structured clearly and logically for machine interpretation

• Free from redundancy, keyword stuffing, or outdated tactics

• Supported by external credibility signals like backlinks and mentions

• Recent and factually accurate
  

If your current content strategy still relies on publishing large volumes of shallow, keyword-heavy copy, it is unlikely to be considered valuable by these systems. Brands must now align their output with AI expectations — prioritising expertise, originality and clarity — to maintain visibility and relevance in search.

How to conduct a comprehensive AI audit.

A proper AI audit requires a structured and methodical approach. Below are the key steps brands should follow to ensure their digital presence is optimised for AI-driven search engines and generative platforms:

Audit your existing content inventory.Export your content list from your CMS or content management tools. Include all pages: blog articles, category pages, product descriptions, landing pages, FAQs, and PR material.Use Google Search Console to identify which pages receive impressions and clicks. Look for underperforming content that may not be indexed or referenced by search engines.Check for AI readability: Use AI-detection tools like Originality.ai or Content at Scale to analyse how readable and extractable your content is for language models.

Review content suitability for AI inclusion.Assess factual clarity and structure. Ensure that key facts, data, and insights are presented clearly in paragraphs or bullet points rather than buried in narrative text.Assign visible authorship. Pages should clearly show who created the content, including job titles and links to author bios where possible.Ensure consistent brand tone. Use tools like Grammarly or Writer.com to maintain clear, professional language. Avoid ambiguity or excessive use of marketing jargon.

Evaluate structured data implementation.Run your top URLs through Google’s Rich Results Test to check for missing or broken structured data.Prioritise schema types relevant to your content:

• Article or BlogPosting for editorial
• Product for eCommerce pages
• Organisation for brand and contact pages
• Author schema where applicable

Ensure consistent markup across templates and check that the structured data matches on-page content.

Conduct a technical SEO health check.Crawl your site using Screaming Frog or Sitebulb to detect crawl errors, broken links, and indexation issues.Use Google PageSpeed Insights to analyse site speed across mobile and desktop. Aim for scores above 80 for both.Test for mobile usability via Google’s Mobile-Friendly Test. Any blocking issues (eg. viewport configuration, tap targets) should be addressed immediately.

Ensure proper canonicalisation to avoid duplicate content signals across product or category variations.

Review off-site signals and E-E-A-T compliance.Identify unlinked brand mentions using search operators like: “YourBrand” -site:yourdomain.com. Reach out to relevant publishers for attribution or backlink opportunities.Ensure authorship credibility. Link author names to relevant profiles (LinkedIn, contributor bios, About pages) and highlight relevant experience or expertise.Review your backlink profile using tools like Ahrefs, Moz, or Majestic. Focus on acquiring links from high-authority domains relevant to your sector.

Monitor AI search visibility.Run branded and non-branded queries on platforms like:

• ChatGPT (with web browsing)
• Gemini (Google Search with AI Overviews)
• Microsoft Copilot (Bing Chat)

Log when your brand appears in AI-generated summaries. Note how your brand is presented and which URLs are referenced.

Review competitors that are cited. Compare their content quality, schema usage, and page authority to yours.

Build a prioritised action plan.Segment tasks by function (eg. content, technical, PR, schema) and assign responsibility across your internal teams or agencies.Prioritise fixes based on potential impact: start with missing schema, slow pages, unlinked mentions, and underperforming high-value pages.Set a review cycle: Re-audit quarterly to keep pace with changes in AI search behaviour and algorithm updates.

By following this structured AI audit process, brands can identify the barriers preventing their content from being recognised and surfaced by machine learning systems — and take practical steps to become more visible in AI-assisted search experiences.

Preparing your strategy for 2025 and beyond.

AI-led search is changing the rules of digital visibility — and brands that rely on outdated approaches risk being left behind. Discoverability is no longer just about rankings; it’s about how well content is understood, selected and surfaced by machine learning systems.

This shift calls for more than small adjustments. It requires a structured approach, technical insight, and a deep understanding of how generative platforms prioritise content. An AI audit offers a clear starting point — helping brands identify where they stand, what’s holding them back, and where to focus next.

Now is the moment to reassess digital foundations and seek the right guidance. With expert support, brands can adapt confidently, stay visible, and continue building trust in an evolving search environment