AI as a new SEO channel: why brands must think beyond Google

Introduction

For more than two decades the world of digital marketing has revolved around one axis – Google as the gateway to the internet. All SEO activities, from technical site optimization through link-building to content marketing, had one common goal: to secure the highest possible position in Google search results. But the digital landscape is changing rapidly. More and more users no longer start their information searches in traditional search engines, but in interfaces powered by generative artificial intelligence – such as ChatGPT, Gemini, Claude, Perplexity or Copilot.
This shift is not just a passing trend; it marks a fundamental transformation in how consumers reach brands, products and services. That is why a new term is emerging: AI-first search – search in which language models (LLMs) become the user’s first and primary point of contact with information.
In this article we will look at why AI is becoming a new SEO channel, what consequences this has for marketing strategies, and what concrete steps brands can take to secure their visibility in the era of AI-driven search.

Why “AI-first search” is changing the rules of the game?

1. From a list of links to a ready-made answer
Classic SEO was based on competing for visibility in SERPs (Search Engine Results Pages). The user typed a query and Google presented a list of links to websites. Marketers’ task was to get their link as high as possible.
With AI it looks completely different. Language models do not return ten blue links – instead they generate a concise, personalized answer, often without the need to click further.

2. Reduction of organic traffic from Google
Market research (Adobe, AP-NORC) shows that in 2024, up to 30% of customers in the tech and lifestyle segments were already using AI assistants to shop for products. In industries such as travel, electronics or fashion that percentage is growing even faster. Every percentage point of traffic shifting from Google to AI is a real loss for brands that do not manage their presence in model-generated results.

3. A new currency – presence in the model
In traditional SEO the page ranking mattered. In the new approach what matters is whether AI mentions the brand and in what context. Does your brand appear as a recommendation? Is it described positively? Or does the model pick a competitor? This “visibility-in-AI currency” is becoming a new KPI for marketers.

History comes full circle: LLMs today and the early days of Google in the 2000s

When Google was just starting out

At the turn of the 1990s and 2000s search engines were still relatively niche. Companies relied mainly on print advertising, industry directories and early online banners. Google, which was then just beginning to build its position, introduced an innovative page-ranking model based on links (PageRank).
At first few companies treated SEO seriously. Those who first understood the potential of optimizing sites for search engines could gain a huge market advantage in a short time. The first online stores, news sites and price comparison services that invested in SEO quickly began to dominate search results. Over time competition increased and the cost of entry – in terms of work and budgets for SEO – rose dramatically.

Analogous situation today – AI-first search

We are now seeing a very similar phenomenon. Language models (LLMs) are in an early adoption phase as a search channel. Many marketers still treat AI as a curiosity, focusing on traditional SERPs. But those who are already investing in AI brand visibility are building the foundations for future dominance.
Just like in the era of “early Google”:

• - Early movers – brands monitoring and optimizing visibility in AI – take a privileged position because their brand starts to be “implicitly” mentioned in model answers.
• - Latecomers – companies that ignore this moment will face a much harder task in a few years, when visibility in AI is already highly competitive and “locked in” by leaders.

Lesson from history: Every change in how information is searched creates a new market hierarchy.

• - 2000–2005 winners were those who quickly understood SEO in Google.
• - 2010–2015 advantage went to brands investing in mobile SEO and social media.
• - 2024 and the years ahead advantage will go to those who first focus on SEO in the world of AI.

How can brands build visibility in AI?

1. Create content that is semantically friendly to LLMs
Language models learn to recognize context and meaning, not just keywords. Therefore:

• - Focus on rich, expert content instead of short posts.
• - Add FAQs that answer common user questions.
• - Use structured data so AI can more easily identify products, services and locations.

2. Monitor brand presence in AI
Just as there are tools to monitor positions in Google, solutions are already emerging to check how AI mentions a brand. Platforms like BrandInAI allow monitoring and auditing of model-generated answers and analysis of the context in which the brand appears.

3. Build expert authority
AI favors brands that are recognized as credible sources. This means you should:

• - publish expert articles,
• - participate in industry media,
• - establish presence in academic publications, reports and citations.

4. Test multiple models
There –is no single “AI-Google.” Each model – OpenAI, Gemini, Claude, Perplexity – can present different answers. Monitoring visibility across several systems in parallel becomes a necessity.

Case studies: how brands are adapting to AI-first SEO

Booking.com: The company invests in integrations with AI assistants so that answers about travel include direct links to their offers. This way Booking doesn’t wait for the user to type a keyword in Google – the brand is present where the user is talking with AI.
Nike: The brand consistently builds an expert narrative around sport and healthy living. In many AI models it appears as the “default” recommendation for people asking about sports equipment, which is the result of years of a consistent content and PR strategy.
HubSpot: A marketing automation platform that consistently builds a library of educational content (HubSpot Academy). As a result it appears in AI models as an example of a leader in inbound marketing – AI cites their articles and guides.
Tesla: A technology brand that, thanks to massive media presence and scientific publications, is almost always mentioned in AI answers related to e-mobility, autonomous cars or renewable energy.
Salesforce: Like HubSpot, it builds expert authority through reports and analyses. In business queries AI often refers to Salesforce as a benchmark for CRM solutions.

Strategic recommendations for marketers

AI assistants are reshaping product discovery and brand perception, so marketing strategies must evolve accordingly. Use the recommendations below to reallocate spend, redefine KPIs, and optimize content and PR for stronger visibility in AI-generated answers

• - Budget allocation: shift part of the funds from classic SEO to monitoring and optimization for AI.
• - New KPIs: instead of asking “what position are we in on Google?”, ask “does our brand appear in AI answers and how is it described?”.
• - Semantic content: create long, in-depth content that models can more easily interpret as valuable sources.
• - Relationships and PR: build brand quotability – models more often recommend entities mentioned in credible sources.
• - Cyclical audits: regularly check brand presence in LLM answers. Treat this the same way you treat social media reputation monitoring.

Where is SEO headed in the AI-first search era?

With the popularization of language models, SEO is undergoing the biggest transformation since Google appeared. The future will no longer be a game of keywords and CTRs, but about whether AI names a brand in its recommendations – and in what context.

Increasingly important will be:

• - semantic and expert content that models interpret as a trustworthy source,
• - AI Share of Voice – the share of answers in which a given brand appears,
• - the combination of SEO, PR and branding, because AI rewards brands present in citations and publications,
• - a winner-takes-all effect – users are more often given one recommendation than a list of 10 links.

This means that in the coming years the advantage will go to those who are already investing in visibility in AI. For latecomers the cost of entry will rise just as it did in the early days of SEO in Google.

Summary

SEO today is at a turning point comparable to the early days of Google more than two decades ago. Back then winners were those who first understood the importance of positioning and started investing in online visibility. Google remains a powerful channel, but AI is becoming the first point of contact with a brand for an increasing number of consumers.
History comes full circle – brands that already monitor and optimize their presence in AI answers are building the foundations for dominance in the years to come.
In the AI-first search era the game of keywords turns into a strategy of building semantic presence, credibility and an expert narrative. New KPIs – such as AI Share of Voice or AI Recommendation Rate – will replace traditional metrics, and the fusion of SEO, PR and branding will become a prerequisite for maintaining competitive advantage.
There is also risk in this transformation: in an AI-first search world the dominance of a few brands may be even stronger than in Google. That means the window of opportunity is limited. Latecomers will face high entry costs, while pioneers will already occupy privileged positions in model recommendations.

So the key question for marketers today is not: “What position are we in on Google?” but: “Does our brand appear in AI answers and in what context?”

That is where - in the conversation between the user and the model – the current transformation in the approach to SEO is being played out.