Editorial
Research Report
Building the Case for Modern Public Sector Messaging
The Gist
- AI readiness gap is wide. Research found only 3% of leading global brands qualify as truly AI-ready, highlighting significant risks in how AI systems interpret and represent organizations online.
- AI visibility cuts both ways. Outdated, contradictory or poorly structured content can be surfaced by AI as fact, creating brand, compliance and customer experience risks that traditional web governance often overlooks.
- Leadership action is urgent. As consumers increasingly begin searches with AI tools and AI-driven traffic grows rapidly, organizations must assess not only how visible they are to AI, but what AI currently understands about their brand.
Benchmarking data reveals that just 3% of the websites from the world's most significant brands can be considered truly AI-ready. Why? Because teams aren't addressing the risks that come with the AI visibility of their digital footprint.
The way consumers search is changing rapidly. McKinsey reports that 50% of consumers are using AI-powered searching.
Digital marketing teams are reacting, focusing on practices such as Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) to make their brand more visible to LLMs and AI tools. Here, there is some overlap with SEO, where many fundamental practices are also critical for GEO.
But is this enough? How truly "AI-ready" are the websites and digital footprints that brands control? Do they meet both the opportunities and the challenges that AI tools and LLMs bring?
Just 3% of Superbrand Websites Are AI-Ready
Analysis I've done suggests that even digital marketing teams from some of the world's biggest businesses are not addressing all the fundamental issues that impact the AI visibility of the brand.
I ran an assessment across the digital footprint of 270 "superbrands" from the UK, US and Europe, covering some of the world's leading companies, including Apple and Barclays.
Only 3% of these sites can be said to be truly AI-ready, that is you can class them as "leading," with a maturity score between 94% and 100%.
This does not mean the remaining 97% of sites are failing with their digital estate; but it does mean there is a lot of work to do in order to be considered "leading" in ensuring AI systems are successfully reading, interpreting, trusting, comparing and representing their brand externally.
Related Article: What 2025 Revealed About AI Readiness Across Marketing and CX
The Flipside of AI Visibility
AI visibility is on the radar of digital marketing teams. We can define this as how accurately, consistently and prominently your brand and organization are found, cited and recommended by AI tools such as ChatGPT, Claude and Gemini, based on your external-facing content, signals and external sources.
AI relies on what it finds across your digital estate as well as third-party content to derive its responses. But AI isn't looking in just the places that your customers are – it is looking at all your content that is accessible and trying to interpret that. So existing content issues across your digital estate have the potential to impact AI visibility.
For example, if you have:
- Out of date, off brand, contradictory, or non-compliant content, then AI tools can surface and present this content as facts in its responses, effectively amplifying messaging you don't want amplified.
- On message content, which is not accessible to AI, then this content will not be found
- Slow or unreliable performing pages, then these may be skipped or incompletely indexed by the AI
- Pages which lack structure and mark-up, then these are more likely to be misinterpreted by the AI.
Related Article: The Mirror Problem: Why Generic Content Can't Win in AI Search
The AI-Readiness Challenge for Superbrands
Organizations that have a mature level of AI-readiness have overcome some of these challenges by taking the necessary action across their digital estate.
And this is what presents a challenge for superbrands. Large, global businesses may have the strongest brand equity, but they also tend to have the most complex information environment and digital estate.
While a smaller organization may have a more manageable number of web pages and documents, a global brand may build up a vast digital footprint, including:
- Thousands of web pages
- A huge archive of years of PDFs
- A network of themed, regional, country and sub-brand level websites
- Archive campaigns
- Investor documents
- Product manuals and support sites
- Partner pages
- ...and so on
Given that brands can build up a significant footprint over time, even assembling a hidden and sprawling digital estate, this represents a significant risk to AI visibility.
Investing in actively managing the murkier and long forgotten corners of this estate may also not necessarily be a priority for digital customer experience, but actions that have been near the bottom of the "to do" list, suddenly assume far greater importance when it comes to AI visibility.
Where AI Supplies Outdated Content
There are already examples circulating where AI tools are returning outdated information with potential consequences.
A financial services organization posted a summer holiday insurance promotion online, but this page was not synchronized with changes to the emergency contact number and changes to the levels of cover included in the contract. AI surfaced the incorrect information, with the potential for people not being fully covered to the level they thought they would be, or having issues reaching emergency support when in difficulty.
Similarly, a retailer had posted safety information about an electrical product across websites, PDFs and supporting documents. Different versions of safety certificates, usage guidance and product information remained available to access. The result was that AI tools accessing these sources surfaced inconsistent safety information to visitors.
These examples sound relatively minor in isolation, but they have the potential for serious consequences and illustrate an issue which is likely to become more prevalent.
Why Leaders Need to Act Now
Editor's note: AI visibility has quickly become a leadership issue. As customers increasingly rely on AI tools to discover, compare and evaluate brands, organizations must address the operational, reputational and commercial risks that come with how AI systems interpret their digital footprint.
| Leadership Priority | What’s Changing | Why It Matters | Key Actions |
|---|---|---|---|
| Pace of Change | Consumer search behavior is rapidly shifting toward AI-first discovery. According to industry research, 37% of consumers now begin searches using AI tools rather than traditional search engines, while 59% believe AI will become their primary way of finding information. Meanwhile, Adobe research found AI-driven traffic to U.S. retail sites increased 393% year over year in Q1 2026. | Customer engagement patterns are changing in real time. Brands that wait for AI adoption to mature risk falling behind competitors that are already optimizing for AI visibility. |
|
| Brand Position | Marketing teams invest heavily in maintaining a trusted, consistent brand experience through websites, content, navigation, search, performance and personalization. Traditionally, these efforts assume customers will visit owned digital properties. | AI tools increasingly bypass websites altogether, presenting information directly to customers. Inaccurate, outdated or contradictory content can be surfaced as authoritative information, potentially damaging brand trust and creating compliance concerns. |
|
| Content Governance Risk | Large organizations often accumulate years of web pages, PDFs, support documentation, campaign assets and regulatory materials. Much of this content remains publicly accessible long after it is no longer current. | AI systems may surface superseded documents, discontinued products, withdrawn guidance or outdated policies as current information. In regulated industries, the consequences can extend beyond brand damage into legal and compliance exposure. |
|
| Commercial Position | Consumers increasingly use AI tools to compare products, services and vendors before making purchasing decisions. As CMSWire recently reported in its analysis of Google AI Mode behavior, searches beginning with the word “which” have increased by 40%. | AI-generated recommendations increasingly shape consideration sets. A brand that is poorly represented—or omitted entirely—from AI responses may never make it into a buyer's evaluation process. |
|
| Competitive Visibility | AI systems are becoming gatekeepers for product discovery, recommendations and research. Visibility is increasingly determined by how well AI understands and trusts a brand's content. | Competitors with stronger AI readiness may gain disproportionate exposure in AI-generated answers, even if they have less traditional brand awareness or lower search rankings. |
|
| Agentic AI | AI agents are beginning to move beyond information retrieval into recommendation, purchasing and transaction workflows. While the long-term impact remains uncertain, the shift could fundamentally reshape how buying decisions are made. | Future AI agents may influence not only which brands customers consider but also which products they ultimately purchase, creating a new layer of competitive risk. |
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| Executive Imperative | Boards are investing heavily in AI initiatives and seeking measurable ROI, yet many organizations have not evaluated how external AI systems currently portray their brand. | Organizations may be investing in AI internally while overlooking how AI externally influences customer perception, trust and buying decisions. |
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Advancing AI Readiness
AI readiness is not something to consider for the future, it is happening now. Given that only 3% of superbrand websites are truly AI-ready, most organizations need to prioritize action.
Leaders focusing on AI readiness have already been considering "What should we do to prepare for AI". But they also need to consider "What does AI understand about us now and what do we need to do to change that understanding?"
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That question is a good starting point – and answering it honestly may be uncomfortable for some teams. Next time I'll explore what to do in more detail; I'll cover a maturity model for AI readiness, and how brands can introduce the right governance to improve AI visibility.
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