What you should be asking about generative search in your organisation

This shift represents one of the most significant changes to digital marketing and public communication since the advent of search engines themselves. Yet many decision-makers remain unaware of how profoundly these changes could affect their organisation's visibility, authority, and ability to reach their intended audiences.

The fundamental shift in search behaviour

Traditional search followed a predictable pattern: users entered queries, reviewed search results, clicked through to websites, and consumed content. This journey created measurable touchpoints and clear attribution paths that organisations could track and optimise.

Today's reality is markedly different. According to recent industry analysis, zero-click searches now account for approximately 27% of all Google searches, meaning more than one in four searchers never leave the search results page. Meanwhile, AI Overviews (Google's AI-generated responses that appear above traditional search results) now trigger for over 13% of queries, with this figure steadily increasing.

The implications extend far beyond simple traffic metrics. When someone searches for "how to apply for planning permission" or "symptoms of diabetes" they're increasingly receiving comprehensive answers directly within search results or AI-generated summaries. Your carefully crafted content might inform these responses, but users never experience your brand, expertise demonstration or calls to action.

How research habits are evolving

The modern information-seeking journey has become increasingly fragmented and platform-agnostic. Users might begin their research with a voice query to their smartphone, continue with follow-up questions to ChatGPT or Claude, verify information through traditional search, and synthesise findings across multiple AI-powered tools before making decisions.

This behaviour is particularly pronounced for what marketers traditionally call "top of funnel" content, i.e. the educational, informational material that builds awareness and establishes authority. Two content types exemplify this shift:

• Guides and How-To Content: Previously, a comprehensive guide on "Energy Efficiency Grants for UK Homeowners" would attract visitors who would spend time reading, potentially downloading resources, and engaging with calls to action. Now, AI systems extract the essential steps, eligibility criteria, and application processes, presenting users with complete answers without requiring site visits. The guide still serves its purpose, but its audience has fundamentally changed from direct readers to AI systems that synthesise and redistribute the information.
• Articles and Analysis: In-depth articles exploring topics like "The Impact of Interest Rate Changes on Small Business Lending" historically built thought leadership through page views, social sharing, and backlink generation. Today, these articles increasingly serve as source material for AI-generated summaries that users receive across multiple platforms. The expertise and analysis remain valuable, but the attribution and brand exposure have become indirect and difficult to measure.

These patterns affect numerous other content types like FAQs, service descriptions, policy documents, and case studies, each experiencing similar transformations in how they reach and influence audiences.

Measuring what matters in a zero-click world

Traditional digital analytics become inadequate when significant portions of your content's impact occur beyond your website's measurement capabilities. Organisations accustomed to tracking page views, time on site, and conversion paths from organic search now face a more complex reality.

The new measurement landscape requires understanding both direct engagement and indirect influence. When your content informs AI-generated responses that help users make decisions, the traditional conversion attribution model breaks down. Users might never visit your website yet still be influenced by your expertise, potentially choosing your services or following your guidance based on AI-mediated exposure.

Forward-thinking organisations are beginning to track metrics like AI citation frequency, brand mention sentiment in AI responses, and cross-platform content attribution. However, these measurements require new tools, methodologies, and analytical frameworks that most organisations haven't yet developed.

Research from BrightEdge indicates that content cited in AI Overviews often comes from authoritative sources with strong E-E-A-T signals, suggesting that organisations investing in content quality and expertise demonstration may benefit from increased AI citation rates, even if this doesn't translate to immediate traffic increases.

The competitive landscape challenge

For organisations operating in competitive markets, the stakes of this transition are particularly high. When AI systems synthesise information from multiple sources to answer user queries, they effectively create a new battleground for visibility and authority.

Consider a user researching "best business banking options in Scotland." Traditional search might lead them to compare websites, read reviews, and evaluate offerings directly. AI-powered responses increasingly provide synthesised comparisons, highlighting key features, costs, and suitability for different business types. The banks and financial institutions whose content most effectively communicates these details to AI systems gain disproportionate representation in these summaries.

This dynamic creates both risks and opportunities. Organisations with superior AI optimisation might capture attention from competitors who remain focused solely on traditional SEO. Conversely, those failing to adapt may find their expertise and offerings increasingly invisible in AI-mediated research processes.

The competitive implications extend beyond immediate visibility. AI systems that consistently cite particular organisations as authoritative sources contribute to long-term brand perception and market positioning. Users who repeatedly encounter a company's expertise through AI-generated responses may develop stronger brand recognition and trust, even without direct website interaction.

Public sector and non-competitive contexts

Organisations without direct competitors, such as local councils, NHS trusts, regulatory bodies, and other public services, face different but equally significant challenges. Their success metrics traditionally focus on user satisfaction, accessibility compliance, and service delivery effectiveness rather than competitive differentiation.

However, these organisations often serve as primary information sources for critical topics that AI systems regularly address. When residents search for "council tax support eligibility" or "NHS appointment booking procedures," the quality and AI-accessibility of official content directly affects public understanding and service uptake.

Poor AI optimisation in these contexts can lead to incomplete or inaccurate information reaching the public, potentially reducing service utilisation or creating confusion about processes and entitlements. Conversely, well-optimised content ensures that official guidance reaches users effectively, regardless of how they choose to access information.

Public sector organisations also have unique obligations around accessibility and inclusive communication. AI optimisation must align with these requirements, ensuring that content serves diverse user needs whilst remaining comprehensible to AI systems that may redistribute the information.

Building organisational readiness

The transition to AI-mediated search requires organisations to evaluate their digital assets through a fundamentally different lens. Content that performs well in traditional SEO metrics may be poorly suited for AI consumption, whilst information architectures optimised for human navigation might create barriers for AI comprehension.

Successful adaptation requires capabilities spanning several disciplines:

• Content Strategy and Creation: Understanding how to structure information for both human comprehension and AI extraction. This includes techniques like front-loading key information, using clear headings and logical hierarchies, and ensuring comprehensive coverage of topics within individual pieces.
• Technical Implementation: Implementing structured data, schema markup, and emerging standards like LLMs.txt that help AI systems understand and utilise content effectively. These technical elements require coordination between content teams and developers.
• Quality Assurance and Accuracy: AI systems amplify both excellent and poor content. Organisations must ensure factual accuracy, currency, and authority demonstration across all digital assets, as errors or outdated information may be redistributed widely through AI responses.
• Measurement and Analysis: Developing capabilities to track AI citations, brand mentions in AI responses, and indirect influence metrics that complement traditional analytics. This requires new tools, processes, and analytical skills.
• Cross-Platform Consistency: Ensuring content performs effectively across traditional search, AI Overview systems, and emerging AI platforms whilst maintaining consistent messaging and authority signals.

At Storm ID, our experience in SEO provides valuable foundation skills for this transition, whilst our thought leadership in data and AI, including collaborative work with initiatives like Futurescot, has developed practical approaches to these emerging challenges. However, the specific skillsets required for generative AI optimisation extend beyond traditional digital marketing capabilities.

The urgency of strategic response

The pace of change in AI-mediated search suggests that organisations delaying adaptation may find themselves at significant disadvantage. Unlike previous digital transitions that occurred over years, AI search capabilities are evolving monthly, with new features and platforms regularly entering the market.

Early indicators suggest that AI systems favour content from organisations that demonstrate clear expertise, provide comprehensive information, and structure content for easy comprehension and extraction. These factors align with quality content principles but require specific implementation approaches that many organisations haven't yet adopted.

The window for gaining competitive advantage through superior AI optimisation may be narrowing as awareness increases and competitors begin their own adaptation efforts. Organisations that begin evaluation and improvement processes now position themselves advantageously for the continuing evolution of search behaviour.

Taking action: starting the conversation

For senior decision-makers reading this analysis, the immediate question isn't whether these changes will affect your organisation, they already are. The question is whether you'll adapt proactively or reactively.

Begin by auditing your current digital content through an AI optimisation lens. Ask whether your most important information is structured for easy extraction and comprehension by AI systems. Consider whether your content demonstrates expertise and authority in ways that AI systems can recognise and utilise.

Initiate conversations within your organisation about measurement methodologies. Are you tracking the right metrics to understand your content's true impact in an AI-mediated environment? Do you have visibility into how your expertise and information reach audiences beyond direct website interactions?

Evaluate your technical infrastructure's readiness for AI consumption. Are your structured data implementations comprehensive? Does your content architecture support both human usability and machine readability?

Most importantly, consider whether your organisation has the internal capabilities required for effective AI optimisation, or whether external expertise might accelerate your adaptation process. The intersection of content strategy, technical implementation, and AI understanding requires specialised knowledge that many organisations are still developing internally.

The transformation of search behaviour represents both challenge and opportunity. Organisations that respond strategically to AI-mediated information discovery will maintain and potentially enhance their ability to reach, influence, and serve their intended audiences. Those that delay adaptation risk diminishing visibility and reduced effectiveness in an increasingly AI-powered information landscape.

The conversation about generative search optimisation in your organisation should begin today. The competitive landscape, or the imperative to serve your community effectively, won't wait for your readiness.

To speak to one of our AI consultants, contact us now.