The Evolution of Search: How AI is Reshaping Brand Visibility and Marketing Strategies

Beyond Google: how brands must rethink search strategies

The ethical use of AI in content creation is perhaps the defining challenge of the media and marketing industry James Reynolds, founder and CEO of SEO Sherpa/Image: Supplied The search landscape is undergoing its most dramatic transformation in decades. For years, Google dominated as the primary gateway to information, but the rise of AI-powered assistants, TikTok, Instagram, and other discovery platforms is reshaping how people look for answers, products, and services. This fragmentation is especially evident among younger generations, who increasingly bypass traditional search engines in favor of social media and conversational AI. For brands, the implications are profound. Search engine optimisation can no longer be confined to ranking high on Google -- it now demands a multi-channel strategy that takes into account new behaviors and platforms. In this exclusive interview, James Reynolds, founder and CEO of SEO Sherpa, unpacks the evolution of search, what Gen Z's habits reveal about the future, and how businesses can adapt to ensure they remain visible in an era where search is everywhere. AI tools like ChatGPT are increasingly being used as search engines. How do you see this shift reshaping how people discover information online? What's reshaping discovery isn't replacement -- it's layered research behavior. We're seeing people use AI tools differently from conventional search. People particularly use AI as a starting point for complex topics, then move to conventional search for specific solutions, and often end up on social or community platforms for peer validation. For example, someone might ask ChatGPT to explain cryptocurrency before they Google "best crypto exchange" or read a Reddit community thread about real-life user experiences. Brands need to completely rethink content strategies because they need to be discoverable at every layer of this journey. The brands we're working with that are winning understand this -- they're creating comprehensive resources that work whether someone finds them through Google, gets them summarised by AI, or discovers them through social platforms. Google's search market share is showing signs of decline. What's driving this trend, and how should businesses prepare? Search itself isn't declining; it's exploding across every platform imaginable. Google alone saw a remarkable 21.6 per cent growth in search volume in 2024, processing over 5 trillion queries annually - 14 billion searches per day and 189,000 searches per second. Recent research from SparkToro confirms that despite predictions of AI cannibalisation, Google still handles 373 times more searches than ChatGPT. But here's the critical shift: while total search volume is surging, it's fragmenting across platforms faster than ever before. The primary driver is generational behavioral change. Gen Z is fundamentally different in how they approach information discovery - 51 per cent prefer using TikTok for search over Google entirely. They're not going to Google to find restaurants - they're checking TikTok. They're not Googling product reviews - they're watching YouTube or scrolling Instagram. Amazon owns product search for most categories. LinkedIn is becoming the go-to for B2B research. Even ChatGPT's relatively small 0.25 per cent market share represents 37.5 million daily search-like interactions - a new behavior layer that didn't exist three years ago. This isn't Google's decline - it's search's massive expansion. For businesses, this means the opportunity is actually bigger than before, but diversification isn't optional anymore. If 90% of your discoverability comes from Google, you're missing the explosive growth happening everywhere else. The brands that are thriving have embraced what we're calling 'search everywhere optimisation.' They're not just ranking on Google; they're discoverable on LinkedIn, optimized for TikTok's algorithm, and building authority across the entire search ecosystem. Search volume is at an all-time high - you just need to be visible where your audience is actually searching. Gen-Z is turning to TikTok and Instagram for search. How should brands adapt their strategies to meet this behavioural change? The fundamental difference is that Gen Z searches for experiences and authenticity, not information dumps. They want to see someone their age using a product, visiting a destination, or solving a problem in real-time. Instead of reading a blog post about "best budget travel destinations," Gen Z watches TikTok vlogs from real people documenting their experiences. They want to see the vibe, not just read the facts. This represents a move from information consumption to experience sampling. The data reinforces this dramatic shift: According to Adobe, 64 per cent of Gen Z use TikTok for search, compared to 49 per cent of millennials. A Forbes study shows that Google usage among Gen Z has now dropped by 25 per cent compared to Gen X. TikTok has a huge impact on purchasing decisions, too, with a study conducted by Morning Consult finding that 72 per cent of Gen Z purchased a product after seeing it on TikTok. Brands need to embrace "social search optimisation" -- both TikTok SEO and Instagram SEO, as we describe them. This means treating these social platforms as search engines and optimising accordingly. Use descriptive captions with natural language that matches how people ask questions. Create searchable content around "how to," "best," and "vs." queries. How you markup your content matters, too -- these platforms are search engines now, so treat them that way. Create content around people's questions. "How to get glass skin in winter" performs better than "winter skincare tips" because that's how people search. Use descriptive captions, location tags, trending audio, and include your target keywords in the words you speak, the video title, and description. Platforms are facing criticism for "stealing" publishers' content, impacting website traffic. What's your perspective on this, and how can publishers protect their value? The data is sobering - AI search engines like ChatGPT and Perplexity send 95.7 per cent less traffic to publisher sites than traditional Google search, with referral rates as low as 0.37 per cent. For context, that means for every 1,000 times your content is used to answer a query, fewer than four people visit your site. But here's what the traffic volume data doesn't tell you: the visitors who click through from AI search are significantly more qualified and convert at much higher rates. While traditional Google search often brings casual browsers who bounce quickly, AI search users arrive with clear intent - they've already received a summary but want deeper information. This creates a fascinating paradox: you're getting fewer visitors, but each one is more valuable. A study from Semrush found that the average AI search visitor (tracked to a non-Google search source like ChatGPT) is 4.4 times as valuable as the average visit from traditional organic search, based on conversion rate. Similarly, Ahrefs recently revealed that their AI search visitors converted at a 23x higher rate than traditional organic search visitors. I believe publishers have more power than they realise. The key is shifting from a purely defensive to a strategic offensive approach. First, publishers need to embrace bot management technology and consider monetisation layers where AI companies pay for content access. Second, the publishers who are thriving have accepted this reality and adapted. Instead of relying purely on discovery traffic, they're building direct relationships with audiences. They're creating experiences that can't be summarised - live events, member communities, interactive tools, and exclusive data. They're also leveraging the authority boost that comes from being frequently cited by AI tools to strengthen their brand positioning and attract high-value partnerships. The real protection is building an audience that comes to you directly, not just stumbles across your content through search. AI-generated content offers speed and efficiency but raises ethical concerns. How can brands use AI responsibly without eroding trust? The ethical use of AI in content creation is perhaps the defining challenge of the media and marketing industry right now. The temptation is enormous - AI can produce content at unprecedented speed and scale. The pressure to scale content production is immense, especially for startups operating with limited budgets. But publishing generic AI content is a massive risk for brand trust and credibility. While artificial intelligence tools are helpful starting points for content research and initial drafts, the magic happens when human expertise intervenes. AI can identify trends or compile statistics, but cannot provide real-world experience and never will. What readers really want to know is how this will impact them specifically - you need a real human expert to explain what these patterns mean and offer real-world practical guidance. What works best is using AI to enhance human capabilities rather than replacing human judgment. How do you see the balance between traditional SEO, social search, and AI-driven discovery evolving over the next five years? The future isn't about choosing between conventional SEO, social search, or AI discovery - it's about balancing all three. Traditional SEO isn't disappearing, but it's evolving. Google remains the dominant force, with almost 90 per cent search market share and 14 billion daily searches, up 21 per cent from last year and 373 times as many searches as ChatGPT. But the nature of search is changing. We're moving toward zero-click searches, where users get answers directly on the results page, and AI Overviews are becoming more prominent. SEO success will increasingly depend on creating content that serves as source material for these AI-generated summaries while providing enough value to drive click-through. Social search will continue growing, especially among younger demographics. By 2030, I predict social platforms will handle 20-25 per cent of all search-like behavior, particularly for local discovery, product research, and lifestyle content. This will require brands to develop "social SEO" capabilities, which means understanding how content is discovered and consumed on each platform. If you were advising a business starting from scratch today, what would your top three priorities be for building a future-proof content marketing strategy? First: Create pillar content pieces that are 10X better than anything else out there. Mr Beast once said, "I'd rather spend 100 hours on a single video and make it the best it can be than spend 10 hours on a video that is just okay." Truly remarkable content doesn't just perform a bit better; it performs many orders of magnitude better than "okay" content. It can also be splintered down into assets that work everywhere. This isn't about repurposing an 800-word blog post into a social media caption. It's about creating something epic that can also work as a short-form video, email, or social post and be structured so AI can understand and cite it properly. Second: Build real authority, not fake authority. Too many brands are still playing the old keyword stuffing and the backlink buying game. Showcase actual humans with real knowledge. Always provide unique insights that your audience can't find anywhere else. And, if you can offer those up with a unique angle or approach, you'll dominate. Third: Use real-time information. The quarterly content calendar is dead. Brands that win are those that monitor social trends, track what's happening in search results, watch creator performance, and adapt their strategy weekly, sometimes daily. This isn't about chasing every viral trend -- it's about having systems that help you spot opportunities early enough to take action. The businesses that will thrive understand that content marketing in 2025 isn't about creating more content - it's about making smarter content that builds genuine relationships across increasingly complex discovery paths.

How to Rank in Google AI Overviews, Chatbots, LLMs

How to Build Topical Authority and Credibility for Your Website? 2025 marked one of the defining years of search fragmentation markets. Instead of Googling for answers as previously, many users actually go first to AI assistants like ChatGPT, Claude, and Perplexity. With that said, it bids one to think of the bigger change occurring in how people search for information, with multiple platforms now trying not just to provide links but to provide synthesized, conversational, and contextualized answers. It becomes crucial to distinguish between these AI-powered search mechanisms for brands and content producers seeking to optimize their visibility and relevance in the new age. Google AI Overviews, for example, are closely integrated with Google's live web index. Traditional search results focus on giving you links ranked by keywords and nothing more. Google's AI synthesizes information from its vast and constantly dynamic index, drawing structured snippets and valuable information to create a single summarized answer in natural language. This approach enables Google to provide users with a brief, synthesized answer to the point of topical knowledge on the web, as perceived at a given moment. Google AI Overviews, which include invitations from several trusted sources, bring a degree of credibility and transparency to the answers given. In contrast, conversational AI assistants like on a fundamentally different architecture. Depending on the version of ChatGPT and the way it is set up, a ChatGPT-type instrument generates a response either from a massive library of pre-trained knowledge or through live information retrieval in real time. While these tools are designed to handle logic and brainstorming, as well as engage users in natural and flowing dialogue, they primarily don't emphasize direct citations or real-time web indexing. These models excel at providing nuanced explanations for a problem, creative solution approaches, and interactive learning experiences, but may lack depth when it comes to references compared to what Google's ecosystem offers. For content creators and brands, this split search ecosystem means that optimizing for Google is no longer sufficient. Visibility in the modern world requires being able to discover and assert authority for content across various AI platforms. This involves creating and publishing high-quality, authoritative content that is easily crawlable and indexed by web indexing systems, while also engaging in professional conversations and developing a broad digital footprint. The content should be flexible enough to assist both in fact extraction, which Google AI Overviews demand, and interactive, reasoning-based answers, which is the realm of conversational AIs. With no single company controlling the entire new AI-centric search landscape, the success of any venture hinges on adopting a networked approach to content distribution. Brands must establish a presence across various channels, including blogs, social media, podcasts, and expert forums, where AI systems aggregate information. This is crucial for building multi-channel authority and gaining citations or synthesis from AI engines in the fragmented search space. Search's present and future are decentered, multiple, and informed by a collaborative network of generative AI engines. For brands, this signifies the modality behind transforming traditional SEO into generative engine optimization that stretches through diverse AI-driven platforms. AI discoverability and an indelible brand authority through this ecosystem shall become the life that shall sustain any brand in the fragmented and conversational search space channel of 2025 and beyond.

Search is being rewritten - and marketers aren't ready | Opinion | Campaign India

As AI reshapes search, brands must move past traditional SEO to engineer discoverability within AI-driven ecosystems and redefine visibility for the future. The digital marketing industry is standing at a decisive point. For years, traditional SEO, performance marketing, and content strategies were the main channels for brand discoverability. Now, those pillars are eroding. Consumer search behaviour is shifting from keyword-centric queries to conversational models powered by AI. The result is that brands can no longer rely solely on Google or its search ranking algorithms to drive visibility. We've entered what I call 'Search Engineering'. This is a deeper, outcome-oriented approach to brand discoverability in AI-first, search-evolved environments. This is not about chasing rankings; it's about being chosen by AI itself. The decline of traditional SEO in an AI-first world Classic SEO has long been about maximising search rankings in the search engine results pages (SERPs) through keywords, backlinks and content relevance. The model assumes a linear, predictable search journey -- type a query, scan a list of links, click one. That journey is disappearing. Generative AI platforms such as ChatGPT, Google's Search Generative Experience (SGE), Microsoft Copilot and Gemini are replacing list-based results with conversational responses. These systems synthesise answers by pulling from multiple sources. A user may never visit a brand's website unless that brand is explicitly cited in the AI's response. This shift moves visibility rules away from pleasing Google's algorithm alone. Instead, the challenge is to structure a brand's digital presence in a way that large language models (LLMs) can recognise, trust and include in their answers. What search engineering really means Search Engineering is the next evolution of SEO -- but with a fundamentally different target. Rather than optimising solely for search engines, it's about ensuring that AI-driven interfaces select your brand when generating answers. This requires: * Structuring data and content so it is accessible to AI crawlers and LLMs. * Optimising for AI outputs, not just search results. * Building topical authority across trusted, verifiable knowledge sources. * Ensuring brand signals are visible in vector-based search models. * Prioritising context, coherence and semantic richness. It's not about cramming in keywords or chasing backlinks. It's about embedding brand signals into the datasets that generative AI tools use. That means making sites, product listings, reviews and expert content machine-readable, up-to-date and credible. Search behaviour has already changed User behaviour is evolving alongside technology. People are no longer 'searching' in the old sense -- they're asking AI to solve problems, recommend purchases, and explain complex topics. A user once might have searched 'best CRM software 2025'. Now, they might ask ChatGPT, 'What's the best CRM software for a mid-sized B2B company with limited onboarding resources?' The AI will combine multiple sources to generate a complete answer, often without linking back to the originals unless specifically prompted. This is a fundamental shift in the buyer journey. Discovery now happens inside AI systems, which are curating -- and in some cases gatekeeping -- what information a user sees. If your brand isn't identifiable in the AI's source data, it might as well be invisible. Why ROAS is losing relevance Performance marketing metrics like Return on Ad Spend (ROAS), click-through rates and conversions were once gold standards. They still matter, but they're increasingly shallow measures in a fragmented, non-linear attention economy. Consumers are bypassing paid channels entirely. Instead of clicking search ads, they're asking ChatGPT for product recommendations. Instead of browsing social ads, they're engaging with Perplexity.ai for peer-informed summaries. These touchpoints rarely show up in conventional performance dashboards. Outcome-based marketing -- including search engineering -- is becoming essential. The priority is no longer impressions or traffic, but ensuring brand presence at the precise moments when AI is influencing consumer choices at scale. The pitfall of content for content's sake Many brands still churn out large volumes of content purely to 'feed the SEO machine'. In AI-driven discovery, that approach is wasteful. LLMs don't reward keyword repetition or freshness alone. They value contextual authority, depth and consistency across sources. Brands that want to influence AI responses need to show up as credible voices, not just prolific publishers. This means authoritative contributions to industry platforms, consistent use of structured data, inclusion in reputable third-party sources, and maintaining a transparent, technically optimised footprint. The relevant question is no longer 'How much can we publish?' but 'How well are we shaping our digital presence to educate AI systems?' Moving beyond the agency model AI-first discovery requires a break from traditional agency models. Agencies have typically focused on execution -- ad campaigns, content production, SEO deliverables. The reality now demands orchestration: aligning brand strategy, data science, creative and engineering in a continuous feedback loop. Marketing operating systems (MOS) are emerging as the new framework. These integrate Search Engineering teams, AI signal intelligence dashboards, real-time brand visibility mapping across LLMs, ongoing content audits, and customer journey tracking across AI touchpoints. The goal is to shift from reactive marketing to proactive visibility management -- influencing the discovery process before a consumer even clicks. This is as much a cultural shift as a technological one. Marketing, engineering, data science and AI strategy teams must work together. Siloed approaches -- performance over here, SEO over there, content somewhere else -- no longer make sense. CMOs and growth leaders need to treat discoverability as an engineering challenge, investing in structured data, machine-readable formats, and the continuous feeding of AI training models with credible, relevant brand signals. Traditional SEO, performance marketing and content strategies are still part of the toolkit -- but they won't get marketers far enough. The future belongs to Search Engineering: a blend of technical fluency and outcome-oriented thinking. As AI becomes the default interface for information discovery, brands that invest early will not just remain visible; they'll help shape the narratives AI platforms deliver. Visibility is no longer earned click-by-click -- it's engineered signal-by-signal, embedded deep in the neural systems that power AI.