The rapid disruption of search marketing
The data is clear and compelling: we are witnessing the most significant disruption to search marketing since Google's inception. According to Gartner's latest CMO Spend Survey, 62% of CMOs are already reallocating budget away from traditional paid search toward AI-powered discovery platforms. This isn't a gradual evolution; it's a market transformation happening now.
As users increasingly turn to AI assistants and LLMs for information rather than traditional search engines, the effectiveness of Google Ads is declining measurably. Enterprises report an average 17% year-over-year decrease in paid search ROI since Q2 2024. By 2027, Gartner predicts that 30% of digital ad spend will target AI-driven channels and LLM-powered walled gardens, up from just 6% in 2023.
For business leaders, this represents both an urgent challenge and a strategic opportunity. Organisations that pivot quickly to new "Generative Engine Optimisation" (GEO) strategies are seeing up to 21% lower customer acquisition costs compared to legacy paid search approaches. Those who fail to adapt risk watching their digital marketing effectiveness erode quarter by quarter.
The time for incremental adjustments has passed. This article outlines the market evidence, business impact, and strategic actions required to thrive in this new landscape.
Market Evidence: How AI/LLM Search is Reshaping Digital Marketing
The shift in user behaviour is unmistakable. According to Forrester's internal "Future of Search" Pulse Survey from July 2025, 42% of US and European users now start their research with an AI assistant or LLM-based tool rather than a traditional search engine, nearly double the 24% reported in January 2024.
This rapid migration is creating a cascading effect across the digital marketing landscape. We're seeing 62% of CMOs actively reallocating budget away from traditional search channels, while paid search ROI has declined by 17% year-over-year. The percentage of digital ad spend directed toward AI and LLM channels is projected to increase from 6% in 2023 to 30% by 2027, representing a significant shift in marketing resources. In Europe, the trend is even more pronounced, with 53% of brands already cutting their search ad budgets. Perhaps most telling is that 42% of users now begin their research journey with an LLM, rather than a traditional search engine, which fundamentally changes the discovery process.
The decline isn't limited to paid search. Organic traffic is also suffering as AI tools provide direct answers rather than sending users to websites. According to the recent Seeking Alpha report, "Companies Find New Avenues to Drive Up Sessions as Google's AI Search Tools Reduce Web Traffic" (August 12, 2025), Google's AI-powered features like AI Overviews and AI Mode are cannibalising traffic to external websites.
The evidence is conclusive: the traditional search-and-click paradigm that has dominated digital marketing for two decades is rapidly giving way to an AI-first discovery landscape.
Business Impact: Winners and Losers in the New Landscape
This market transformation is creating clear winners and losers. Organisations that recognise the scale and speed of this disruption are gaining a competitive advantage, while those clinging to outdated search marketing playbooks are seeing diminishing returns.
Skyscanner's experience provides a compelling case study of successful adaptation to this new reality. In early 2025, the travel comparison site faced a challenging reality: its Google Ads performance was deteriorating despite increased investment. The company made a bold decision to shift its budget away from Google Ads toward partnerships with Bing Copilot and Perplexity AI. The results were striking. Within six months, non-Google AI-powered referral sessions accounted for 18% of web bookings, with acquisition costs per booking down 23% versus Google Ads. By optimising content specifically for AI summarisation and creating structured data feeds for LLMs, Skyscanner positioned itself as a preferred information source for travel-related queries in the AI ecosystem.
The Guardian offers another instructive example of strategic pivoting in response to changing search dynamics. Facing a 17% decline in traffic attributed to Google's AI features, The Guardian ramped up newsletter, app push, and direct engagement campaigns. This pivot to owned channels paid off with subscriber conversion via these direct channels increasing by 29% year-on-year. "We realised that waiting for Google to solve our traffic problem wasn't a strategy," said a Guardian executive. "By doubling down on direct relationships with readers, we've not only offset the search decline but built more valuable, long-term audience connections."
The financial impact of this shift is becoming increasingly clear across the industry. An internal report by BARC claims that best-in-class European companies are seeing up to 21% lower customer acquisition costs from AI-driven channels than from legacy paid search. Forrester's analysis shows that 39% of digital advertisers have reduced Google Ads budgets in H1 2025, with 29% actively investing in "GEO" and AI-native brand content.
As reported by the Financial Times, Google’s AI-powered search features like AI Overviews and AI Mode are increasingly providing direct answers, reducing referral traffic to websites. The Wall Street Journal similarly highlights that AI-based summaries atop search results are causing notable drops in click-through rates, leading marketers to explore new frameworks such as GEO, AEO, and AI SEO.
The message is clear: continuing to invest heavily in traditional search marketing while underinvesting in AI-ready content and platforms is increasingly a losing proposition.
Strategic Response: From SEO to GEO
The emergence of "Generative Engine Optimisation" (GEO) represents a fundamental shift in how brands must approach digital visibility. As detailed in Practical Ecommerce's August 12, 2025, article "Is GEO the Same as SEO?", this new discipline requires different strategies and capabilities.
Unlike search engines, Large Language Models (LLMs) don't have an index or cache of URLs. When they search, they use external search engines, then read and synthesise the content. This fundamental difference has profound implications for how content must be structured and optimised.
Ann Smarty, Search Analyst & Editor at Practical Ecommerce, puts it succinctly: "Generative Engine Optimisation is fundamentally different from SEO. LLMs don't reward classic keyword strategies; they reward clarity, authority, and structured knowledge."
Content structure has become significantly more important than keywords in this new paradigm. LLMs prioritise well-structured, clearly organised information that they can easily parse and synthesise. This means that the way information is presented with logical hierarchies, clear relationships between concepts, and comprehensive coverage of topics matters more than traditional keyword density or placement.
Authority signals have shifted from links to accuracy in the AI-first landscape. While backlinks remain important, LLMs also evaluate content based on factual consistency, comprehensive coverage, and alignment with trusted sources. Content that demonstrates expertise and provides thorough, accurate information tends to be favoured by AI systems, even if it doesn't have the strongest backlink profile.
Structured data has become essential rather than optional. Content that includes schema markup, clear hierarchies, and machine-readable formats is more likely to be referenced by AI systems. This structured approach helps LLMs understand the relationships between different pieces of information and makes it easier for them to extract and synthesise key points.
The nature of content itself must evolve, with direct answers outperforming clickbait in AI-powered environments. Content designed to provide comprehensive answers rather than tease clicks performs better when AI systems are evaluating and synthesising information. This represents a significant shift from traditional SEO approaches that often focused on driving clicks rather than providing complete information.
According to Gartner's client research, nearly half of large enterprises have already established a dedicated team or lead for Generative Engine Optimisation (GEO), underscoring the need for specialised content strategies in the AI discovery era.
Leadership Action Plan: Five Critical Steps
The evidence is clear, and the strategic imperatives are emerging. Marketing and digital leaders must take decisive action now to position their organisations for success in this rapidly evolving landscape.
The first critical step involves reallocating budget and resources to align with changing user behaviour. The traditional digital marketing mix needs immediate recalibration. According to Forrester, top areas for new investment include partnerships with AI-powered platforms like Perplexity, Bing Copilot, and Anthropic's Claude; AI-driven marketplace integrations; content optimised for AI summarisation; and direct engagement channels such as newsletters, apps, and communities. Organisations should conduct an urgent audit of their Google Ads performance, looking specifically for declining ROI trends, and shift resources to channels showing growth potential. This isn't about abandoning Google entirely, but rather about diversifying digital presence to reflect the fragmented nature of modern search and discovery.
Developing GEO capabilities represents the second critical action area for forward-thinking organisations. In comments reported by industry outlets, Pacvue President Melissa Burdick emphasised that adapting to AI-powered search approaches is no longer optional for marketers—those who move fastest will lead. This adaptation requires new skills and capabilities across the organisation.
Content specialists must understand AI summarisation and LLM behaviour to create material that performs well in AI-generated responses. Technical teams need expertise in implementing structured data and schema markup to make content more machine-readable and AI-friendly. Analytics experts must develop proficiency in tracking new metrics like "LLM Brand Mention Share" and "AI Answer Inclusion Rate" to measure success in the AI discovery landscape. BARC identifies these new metrics as key KPIs for 2025, reflecting the need to measure success differently when users may consume brand information without ever visiting a website.
The third strategic imperative involves strengthening first-party data and direct relationships with customers. As Google's role as intermediary diminishes, the value of direct customer relationships increases dramatically. According to Gartner client research, a growing majority of brands are stepping up investments in first-party data collection and CRM systems—primarily to counteract declining performance from search-driven acquisition. This shift requires enhanced data collection across owned touchpoints to build a more complete understanding of customer behaviour and preferences.
Organisations need improved customer identity resolution capabilities to connect interactions across channels and devices. More sophisticated segmentation and personalisation capabilities are essential to deliver relevant experiences that drive engagement and conversion. Perhaps most importantly, brands must develop stronger value propositions for direct engagement that give customers compelling reasons to interact directly rather than through intermediaries.
Forging strategic AI platform partnerships constitutes the fourth critical action area in the evolving search landscape. The fragmentation of search across multiple AI platforms creates both challenges and opportunities for marketing leaders. Forward-thinking organisations are establishing direct relationships with emerging AI platforms to ensure favourable positioning. This might include content licensing agreements with major LLM providers to ensure brand information is accurately represented.
API integrations with AI assistants and search tools can provide privileged access and visibility. Co-marketing initiatives with emerging platforms help build presence in new ecosystems. Early adopter programmes for new AI features allow organisations to gain experience and advantage before competitors. These partnerships represent a new frontier in digital marketing, requiring different skills and approaches than traditional search engine relationships.
The fifth essential step involves implementing new measurement frameworks that capture performance in an AI-first world. Traditional search metrics are increasingly insufficient for understanding how brands perform when users may consume information without ever clicking through to a website. Organisations need new measurement approaches that capture the full customer journey across traditional and AI-powered touchpoints.
According to BARC, leading European companies are now tracking "LLM Brand Mention Share" to understand how often the brand is mentioned in AI responses. They measure "AI Answer Inclusion Rate" to determine the frequency with which brand content is used to generate answers. "Session Recapture Rate" helps quantify success in driving traffic through non-Google sources as traditional search traffic declines. These metrics provide a more holistic view of digital performance in the evolving landscape and help organisations adapt strategies based on meaningful data.
Looking Ahead: The Next 18 Months
The pace of change will only accelerate. Based on current trends and expert forecasts, the search landscape will continue to evolve rapidly over the next year and a half.
Further fragmentation of search is inevitable as more AI platforms enter the market and existing players refine their offerings. The days of Google's near-monopoly on search are ending, replaced by a diverse ecosystem of specialised AI tools and assistants. This fragmentation will create both challenges and opportunities for marketers, requiring more nuanced approaches to digital presence and discovery.
We can expect the emergence of new ad formats specifically designed for conversational and assistive interfaces. Traditional search ads were built for a list-based results page, but AI interfaces demand different approaches to sponsored content and recommendations. These new formats will likely be more integrated with the conversational flow and contextual needs of users, requiring marketers to rethink creative and targeting strategies.
The consolidation of GEO practices is expected to accelerate as the market matures. What is now an emerging and somewhat experimental field will develop more standardised approaches to optimisation as practitioners identify effective techniques and share knowledge. Organisations that invest in developing GEO expertise now will be well-positioned to benefit from this consolidation and establish leadership in the field.
The integration of search and commerce will continue to blur the lines between information seeking and transaction. AI assistants will take on more shopping and comparison functions, potentially disrupting not only search but also e-commerce platforms. This convergence will create new opportunities for brands to connect with customers at the moment of decision, but will require sophisticated strategies that blend informational and transactional content.
Decisive Leadership Required
The disruption of traditional search marketing by AI-powered alternatives represents one of the most significant shifts in digital marketing since the rise of social media. The data is unambiguous: user behaviour is changing rapidly, and the effectiveness of traditional approaches is declining.
This is not a moment for incremental adjustments or wait-and-see approaches. It demands decisive leadership and strategic pivots. Organisations that recognise the scale and speed of this transformation and act accordingly will not only weather the disruption but also emerge stronger and more competitive.
The question for leaders is not whether to respond, but how quickly and comprehensively they can transform their digital marketing approach for the AI-first era. The winners in this new landscape will be those who act with urgency, invest with foresight, and execute with precision.
About the Author
Bruno Dehouck is the CEO of Keyrus UK and Iberia, a global leader in data intelligence, digital experience, and management & transformation consulting. With over 25 years of experience guiding organisations through digital transformation, Bruno is passionate about helping clients leverage data and AI to create a sustainable competitive advantage.
If you wish to connect directly with Bruno Dehouck, then click here.
Sources
1. "How Marketers Are Reacting to Google's Rosy Picture of AI Search Impact" - Ad Age, August 14, 2025
2. "Is GEO the Same as SEO?" - Practical Ecommerce, August 12, 2025
3. "Companies Find New Avenues to Drive Up Sessions as Google's AI Search Tools Reduce Web Traffic" - Seeking Alpha, August 12, 2025
4. Gartner "Hype Cycle for Digital Marketing 2025", "CMO Spend and Strategy Survey Q3 2025"
5. Forrester "Future of Search Pulse Survey", "North American Digital Advertising Forecast Q3 2025"
6. BARC "European Digital Marketing Monitor Q3 2025", "AI Discovery and Ad Effectiveness Survey"