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Recent Searches
AI-powered search and large language models are changing how consumers discover, evaluate and choose brands. Organisations that fail to adapt risk becoming invisible in AI-generated responses, while those that do can strengthen brand presence, trust and influence at scale.
In this article, we explore:
- How consumer behaviour is changing as AI-powered search becomes a more prominent part of the buyer journey, particularly for product research, comparison and recommendations.
- The emerging challenges for brands, including reduced website traffic from zero-click searches, the need to appear in both brand and non-brand AI queries, and the growing importance of AI-ready content.
- Five practical principles to improve AI visibility, including AEO and GEO, AI-optimised content, new measurement frameworks, technical readiness and website crawlability.
- How brands can manage reputational risks associated with AI-generated responses, including misrepresentation, outdated information and the influence of user-generated content.
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Chapter 1
The Shift to AI-Search: How Consumer Behaviour is Changing
How AI is changing the way consumers discover, compare and choose brands
How much influence does AI have in your purchasing decisions?
AI-powered search engines and LLMs have emerged as a critical early touchpoint in the customer journey, from discovery and consideration to conversion. Consumers increasingly use AI search to compare products according to their specifications and budget, assess brand reputation and evaluate alternatives before making a purchase. AI search attracts high-intent shoppers because it reduces the number of steps between research and purchase.
As AI becomes the new front door to search, brands are no longer merely found, they are interpreted. Customers increasingly meet your brand through AI before they meet you. Understanding how that narrative compares to competitors is now foundational to modern brand and growth strategy.
Richard W Hepworth
Customer Transformation Partner
Specific user intents emerge with the use of AI-powered platforms
Recent studies have discovered that by the end of 2025, users in AI-mode are showing a higher probability of buying a product/service with higher conversion rates than traditional web users1. Users of AI can typically be categorised based on their specific motivations2.
Trust in AI platforms is rising
Trust in AI recommendations is rising, particularly in the UK. Research found that 58% of UK consumers are comfortable receiving AI-generated product suggestions, with 38% willing to add recommended items directly to their basket3. By contrast, EY's recent study on AI users in Ireland shows that while AI adoption is high, trust in AI-driven decision-making remains more limited. Although 84% of Irish respondents reported using AI in the previous six months, many remain cautious when engaging with unfamiliar brands and only 8% would trust an AI agent to buy a product on their behalf, despite 12% already using AI to automate online shopping tasks4.
Consumer Behavioural Shifts and Consequent Brand Challenges
As consumer behaviours shift with the use of AI, several brand challenges emerge for visibility in the AI landscape.
Brands are fearing invisibility in the AI era
Many organisations understand the importance of AI visibility but remain uncertain about how to influence it. As AI becomes a key point of discovery, brands need to understand how they are represented in AI-generated responses and recommendations.
Customers today are increasingly turning to AI not just to search, but to sense-check decisions, compare options, and guide what they do next and they're placing real trust in what comes back. That creates a powerful opportunity for CMOs. Your data and content are the signals shaping how your brand is understood in these interactions – they’re how your brand is represented at a critical point in the buyer journey. The brands that are actively optimising for AI influence the choices customers make.
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Chapter 2
5 Principles to Achieve Brand Visibility in the AI Era
A framework for improving AI visibility, trust and brand representation
Many organisations are still developing their approach to AI visibility. The following five principles provide a practical framework for increasing visibility, improving brand representation and managing risk in AI-driven environments.
5 Principles for Navigating Brand Challenges in the AI Era
- Principle 1
- Principle 2
- Principle 3
- Principle 4
- Principle 5
Principle 1: AEO & GEO – The New Terms for AI Visibility
As AI searches disrupt how people discover information, brands must ensure that their content is structured, trusted and understood by AI engines for Answer Engine Optimisation (AEO) and Generative Engine Optimisation (GEO), making visibility in AI powered results a strategic outcome.
A Shift from SEO to SRO
SEO remains essential to ensure a brand's content is discoverable in Search Engine Results Pages (SERPs). However, AI engines do not retrieve answers to queries by matching key words. Instead, they select content that is most probable to answer a query. This shift from deterministic ranking to probabilistic retrieval is called Semantic Retrieval Optimisation (SRO).
As a result, brands need to re-shift their Digital Marketing Strategy beyond SEO to include SRO; focusing on increasing the probability of their content to be retrieved by AI engines whilst also appearing in SERPs.
Principle 2: Create AI-search optimised content
The AI-Optimised Content Writing Capability Gap
CMOs, content writers and CX teams need new capabilities to create authoritative content that AI platforms can easily identify, trust and surface. Challenges within this capability include:
- Understanding how AI selects and presents information,
- Maintaining content visibility,
- Balancing resources, and
- Measuring AI’s impact on customer journeys and ROI.
Closing this AI gap requires skills in AI content optimisation, data analysis, and agile content management.
Principle 3: Track new metrics measuring AI visibility
Success in AI visibility requires a new set of metrics that reflects how content is interpreted, selected, and presented by LLMs or AI overviews. By tracking the emerging KPIs below, brands can have a better understanding of their presence across AI-generate responses, brand prominence and sentiment, and continuously optimise for this new layer of digital visibility.
Principle 4: Optimise website crawlability and build the right tech integrations
Technical readiness influences AI visibility
As AI becomes the primary interface for discovery, visibility is no longer driven solely by search rankings. Brands must ensure that their websites are crawlable and indexable, meta data must be clear and product data should be up to date. Otherwise, brands risk being excluded from recommendations before customers ever reach them.
Key Insight: AI platforms rely on structured, crawlable data and API integrations to surface relevant products and services. Technical readiness is now a commercial driver of visibility, not just a backend SEO requirement.
Principle 5: Mitigate the risks of AI brand visibility
User Generated Content and brand content can be misinterpreted
Even if brands achieve visibility in AI-generated responses, they remain exposed to reputational risks. AI systems may misinterpret brand-owned content, user-generated content (UGC) or outdated information, leading to inaccurate, incomplete or misleading representations of a brand. As AI increasingly shapes consumer perceptions at scale through recommendations, comparisons and summaries, organisations face a growing challenge in maintaining control of their brand narrative. Proactively monitoring AI-generated responses, ensuring authoritative content remains current and addressing inaccurate or negative signals are becoming essential to protecting brand reputation and sustaining trust.
Key Insight: Brands can actively manage their AI presence by continuously monitoring both AI platforms and UGCs for inaccurate content pertaining to the brand. In addition to this, maintaining high authority content and up-to-date facts can lessen this risk. Brands can also consider monitoring the overall sentiment of UGCs for insights on brand perception and user reviews.
- Grill, A. (2025). AI before you buy: More than a quarter of Brits happy to let AI buy on their behalf. [online] Kingfisher.com. Available at: AI before you buy: More than a quarter of Brits happy to let AI buy on their behalf – Kingfisher plc [Accessed 28 May 2026].
- How AI users in Ireland are shaping the next phase of adoption | EY - Ireland
- Adobe Digital Insights (2026). Quarterly AI Traffic Report. [online] Business.Adobe.com. Available at: https://business.adobe.com/resources/sdk/adobe-ai-traffic-report.html.
- ACM Digital Library, n.d. A New Taxonomy of Web Search: A User-Centered Framework for Search Intent in the AI Era. [Online]. Available at: https://dl.acm.org/doi/10.1145/3772318.3791050
- Kuzminov, M. (2025). Rethinking Brand Visibility Amid The Rise Of AI Search. Forbes. [online] 18 Sep. Available at: https://www.forbes.com/councils/forbesagencycouncil/2025/09/18/rethinking-brand-visibility-amid-the-rise-of-ai-search/ [Accessed 28 May 2026].
Summary
AI is changing how consumers encounter and assess brands. By improving content, measurement, technical foundations and oversight, organisations can strengthen their presence in AI-generated results while reducing the risk of inaccurate or outdated brand information.
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