SEO copywriting in the AI era: a guide to GEO

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The new horizon of digital content: how artificial intelligence is redefining strategies and opportunities in SEO and copywriting

 

A man views Google's AI Mode on his smartphone

Artificial intelligence (AI) is radically redefining the landscape of online search and content marketing. The era of traditional SERPs, where the goal was to rank first on Google, is rapidly giving way to a new challenge: becoming the primary source of choice for AI to generate direct and concise answers for users.

In this scenario, simply optimizing content for traditional search engines is no longer enough. It’s necessary to create content that’s not only engaging for people, but also easily interpreted and enhanced by generative search engines. This practical guide helps you understand how to produce content that stands out in new searches, is AI-friendly and GEO-ready, and can combine the power of human-generated content with the needs of next-generation algorithms.

The AI ​​landscape of online search: from SERPs to AI Overviews

In recent years, online search has undergone an unprecedented transformation thanks to the advent of artificial intelligence. Traditional SERP results are giving way to new ways of presenting information that are increasingly rapid, personalized, and concise. Generative AI is redefining the rules of the game, offering users immediate and detailed answers, and forcing digital content producers to rethink their strategies and priorities. In this dynamic environment, it is essential to understand how new AI Overviews work, their impact on organic traffic, and the opportunities offered by Generative Engine Optimization (GEO).

AI Overview: the new reality of Google Search

Google is revolutionizing online search with the introduction of AI Overviews, a feature based on generative artificial intelligence (now powered by the Gemini 2.0 model). These concise and structured answers appear directly in the SERP, combining information from multiple sources to offer an immediate and comprehensive overview.

Practical example

Imagine searching Google for: “What are the characteristics of J.S. Bach’s harmony?”
With the AI ​​Overview, instead of a simple list of links, we receive a concise response that gathers and summarizes key points from various authoritative sources:

  • The refined use of counterpoint
  • The richness of modulations
  • The polyphonic structure
  • The balance between the voices
  • The harmonic innovation compared to his contemporaries. This approach allows the user to immediately obtain a complete and reliable overview, without having to explore multiple sites or documents.

 

Google's AI Overview

 

Therefore, the primary goal is to reduce the steps required to obtain answers, accelerating information access and responding to the competitive pressure of new players like SearchGPT or Perplexity AI.

One of the key innovations is the “query fan-out” technique: AI breaks down a complex question into sub-questions, simultaneously analyzes multiple sources, and constructs a structured and organic response. At the same time, “AI Mode” introduces a conversational and interactive dimension, allowing users to delve deeper into topics through direct questions and answers with AI, updated in real time with fresh data.

The impact on organic traffic and user behavior

Initial studies show that the presence of an AI Overview reduces the number of clicks on traditional results, with an average drop in CTR of 7-10% for informational searches.

This phenomenon is leading to the rise of so-called “zero-click searches”: many answers are answered directly in the SERP, without the need for further navigation. For content creators, the challenge has shifted: it’s no longer enough to be in the top 3 results; they must understand how and why AI selects, summarizes, and presents content.

An interesting finding: clicks that occur when an AI Overview is present tend to be more qualified: users who decide to delve deeper are more engaged and spend more time on the sites they visit.

Introduction to Generative Engine Optimization (GEO)

This is where Generative Engine Optimization (GEO) comes in, a new paradigm that complements (and doesn’t replace) traditional SEO. While traditional SEO aims to position web pages in organic search results, GEO focuses on optimizing content so that it is selected and integrated into the responses generated by AI (such as ChatGPT, Gemini, or Perplexity AI).

Traditional SEO vs. GEO: comparison table

Aspect

Traditional SEO

GEO (Generative Engine Optimization)

Main objective

Rank pages in organic SERP results Get content selected and integrated into AI responses

Target audience

Search engines and human users Generative AIs and end users

Optimization focus

Keywords, meta tags, backlinks, technical structure Clarity, synthesis, structured data, direct answers

Success measurement

Ranking, CTR, organic traffic Selection in AI Overviews, visibility in AI responses

Rewarded content type

Content optimized for keywords and structure Original, reliable, easily synthesizable content

Update frequency

Periodic, based on algorithm changes Continuous, in response to queries and real-time data

Human role

Central in creation and review Central in supervision, strategy, and quality control

Main tools

Google Search Console, SEMrush, SEOZoom, Ahrefs ChatGPT, Gemini, Perplexity, MarketMuse, schema.org

Main risk

Loss of ranking due to algorithm updates Exclusion from AI responses, invisibility in new engines

 

GEO is based on the generation of personalized content in real time, modeled on user intent and interactions. According to projections, traditional search volume could decline by 25% by 2026, in favor of increasingly AI-driven search.

Projected annual visitors by source

Source: Semrush Blog, “We Studied the Impact of AI Search on SEO Traffic. Here’s What We Learned”.

 

SEO and GEO must coexist synergistically: SEO ensures visibility, GEO adds contextual relevance and personalization, helping content stand out in direct AI responses.

The foundations of AI-friendly copywriting: quality and search intent

To stand out in the new era of online search, simply writing for search engines is no longer enough: it’s necessary to design content that meets the needs of both people and artificial intelligence. AI-friendly copywriting requires an approach that combines quality, reliability, and a deep understanding of user search intent. In this context, the ability to create original, authoritative, and truly useful copy becomes the true differentiator. Let’s analyze the fundamental principles for developing content that can be recognized, valued, and selected by next-generation AI.

The imperative of quality and reliability

In the age of AI, content quality has never been more important. Google rewards content that adheres to the E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) principles: real experience, expertise, authoritativeness, and reliability are the cornerstones of being selected both in SERPs and in AI responses.

Originality is another distinguishing factor: AI favors content that offers proprietary data, unpublished analyses, and clear explanations of “how” and “why.” Generic statements, vague advertising claims, and half-truths are ignored: AI seeks verifiable, detailed, and concrete information.

Anticipating search intent in the conversational age

Today, keywords are no longer enough. It’s essential to understand and anticipate search intent, offering comprehensive, contextually rich answers that cover all facets of a topic. Semantic research becomes crucial: it’s necessary to build a “semantic map” that includes synonyms, related concepts, and all possible sub-questions a user might ask.

AIs are designed to handle conversational and multi-turn queries, i.e., sequences of questions and answers. Content must therefore be structured to answer primary questions and anticipate subsequent ones, capturing the “solution” intent of users seeking immediate and practical solutions.

To get the most out of this approach, one possible solution is to provide a comprehensive “pillar page” for each macro-content, divided into clear and easily navigable sections via an initial table of contents and hierarchical headings (H2, H3, H4). This way, both users and AIs can quickly find relevant information related to the topic in question. For vertical insights or very specific questions, it’s useful to create dedicated pages linked internally to the main page: this strategy, known as “topic clustering”, improves the user experience and increases the likelihood that content will be selected by AI to answer complex and conversational queries.

SEO copywriting techniques for AI optimization (GEO-ready)

With the evolution of generative AI, SEO copywriting techniques must adapt to new criteria for readability and content selection. Today, writing for the web means structuring texts that are easily understood by both algorithms and human users, focusing on every aspect, from clarity of exposition to relevance of information. The goal is to make content not only SEO-friendly, but above all GEO-ready, meaning optimized for selection and valorization by the new artificial intelligences that govern search. Let’s explore which strategies to adopt to make our content truly competitive in the AI ​​era.

Content structure for AI readability

To make content easily interpretable by AI, it’s essential to adopt a clear and organized structure. Here are some practical tips to improve readability for both algorithms and users.

  • Clarity and Hierarchy: Use well-organized headings (H1) and subheadings (H2, H3). A clear structure makes it easier for AI to extract information and improves readability for users.
  • Concise sentences and short paragraphs: Prefer streamlined syntax. Short paragraphs that focus on a single concept help both AI and human readers.
  • Bullet points and numbered lists: Information organized in lists is more easily recognized by algorithms and increases the likelihood of being selected in AI responses.
  • Initial summaries: Introducing key ideas right from the start (for example, in a summary box) makes it easier for AI to work and increases the chances of being selected as a snippet or in AI Overviews.

Relevant and engaging content

Beyond form, substance matters: content must be useful, up-to-date, and capable of answering users’ questions in depth. These principles help create texts that capture the attention of AI and the public.

  • Focus on “how” and “why”: AI values ​​content that explains processes and motivations, not just superficial descriptions.
  • Frequency and updating: Freshness of information is crucial. Regularly update your content with new data and perspectives to maintain relevance.
  • Conversational writing: Use natural language that directly answers questions. Integrating FAQ-style questions and answers helps both traditional SEO and the new AI-driven search.

Multimedia optimization and structured data

Visual elements and structured data also play a key role in GEO-ready optimization. Below are some best practices to ensure all your content, including multimedia, is accessible and enhanced by AI.

  • AI-friendly descriptions: Images, videos, and podcasts require alt text, captions, and descriptive metadata. AI doesn’t “see” visual content without textual support.
  • Schema Markup: The use of structured data (schema.org) helps AI better understand and present information, making it easier to include content in summary responses.
  • Accessibility: Avoid barriers like rigid paywalls or complicated logins. An accessible site makes it easier for AI to index and select content.

The indispensable role of humans in the AI ​​era

Despite the extraordinary advances in artificial intelligence, the human component remains central to creating valuable content. Machines can automate processes and support optimization, but it is humans who ensure authenticity, originality, and a true connection with the audience. In an environment where AI is increasingly present, understanding the irreplaceable role of the human element becomes essential to stand out and build an effective and sustainable content marketing strategy.

AI as a tool, not a substitute

Artificial intelligence is a powerful tool, but it cannot replace the creativity, intuition, empathy, and deep understanding of the audience that only humans possess. Human oversight remains essential for defining search intent, choosing the right keywords, ensuring originality and user value, and “humanizing” AI-generated content.

Today, most users easily recognize AI-generated content (over 70% for images, over 82% for text). Google, for its part, penalizes sites that rely entirely on AI without human review, potentially damaging the brand’s reputation.

The hybrid approach: human content marketing + GEO content marketing

The key to standing out in the new research is the synergy between creating authentic and engaging content (Human Content Marketing) and optimizing for AI-driven search engines (GEO Content Marketing). Comprehensive, well-documented analysis with an authoritative perspective is essential to stand out.

Tools and monitoring for successful AI copywriting

To achieve tangible results in AI-optimized copywriting, it’s not enough to simply create quality content: it’s essential to rely on advanced tools and adopt a data-driven approach. Keyword analysis, performance monitoring, and continuous updates are key to maintaining competitiveness and ensuring your content remains relevant to users and algorithms. Let’s explore which tools can support each stage of the process and how to set up effective monitoring to quickly adapt to changes in the digital landscape.

Tools for research and analysis

To build an effective AI copywriting strategy, it’s essential to choose the right tools that support every step, from keyword research to data analysis. Here’s an overview of the main solutions that can help you identify opportunities, generate ideas, and optimize your content in a data-driven way.

  • Keyword research and intent: Tools like Google Keyword Planner, Google Suggest, Google Trends, and UberSuggest are essential for identifying the most relevant keywords, analyzing search volumes, and identifying emerging trends in your industry. Beyond keywords, it’s now essential to analyze associated search intent to understand the questions and needs behind user queries. Integrating this data into your content strategy allows you to anticipate both user and AI needs.
  • AI for insights and ideas: Platforms like ChatGPT, Gemini, and Copilot are valuable tools for brainstorming and organizing concepts. They can be used to generate content ideas, simulate user questions, build semantic maps, or suggest engaging titles. However, it’s important to remember that these AIs don’t provide precise data on search volumes or real trends; they must therefore be integrated with quantitative analysis tools for a comprehensive strategy.
  • Advanced data analysis: Solutions like Quadro, Microsoft Power BI, Akkio, MarketMuse, and Clearscope allow you to collect, visualize, and interpret large amounts of data, profile customers, identify behavior patterns, and plan data-driven strategies. These tools allow you to evaluate the quality and relevance of content, identify opportunities for improvement, and scientifically measure the impact of copywriting and SEO efforts.
  • SEO Tools: Platforms like SEMrush and SEOZoom offer advanced features for monitoring SERPs, which are increasingly influenced by artificial intelligence. They allow you to analyze which queries and topics are prioritized by AI, monitor the positioning of your content compared to that generated by AI, and identify new keywords or search intent to work on. They also allow you to track performance compared to competitors and quickly adapt your strategy.

Continuous monitoring and adaptation

Once content is published, the work isn’t over: constantly monitoring performance and updating strategies is essential to staying competitive. Below are some best practices and useful tools for measuring results and maintaining quality and relevance over time.

  • Measure performance: Constantly monitoring content performance is essential to understand what’s working and what can be improved. Tools like Google Analytics and Search Console allow you to analyze key metrics such as conversions, time spent on the site, bounce rate, and traffic sources. In particular, it’s useful to observe user behavior from AI Overviews: these clicks are often more qualified, with users more engaged and likely to take valuable action on the site.
  • Combat content decay: Content decay is the natural decline in content performance over time, due to information obsolescence or the emergence of new competitors. To combat it, it’s important to regularly update content, integrate new data, respond to emerging questions, and constantly monitor organic visibility. Only in this way can we ensure that AI continues to select and enhance its content in synthetic responses, maintaining the site’s relevance and authority over time.

The future is collaboration and the union of knowledge, both human and technological

SEO, far from being obsolete, is undergoing one of its most profound and decisive evolutions: Generative Engine Optimization (GEO) has become the new frontier of digital optimization. In this context, the real challenge is not just adapting, but synergistically integrating human skills with the capabilities of artificial intelligence. Success in the next-generation online search landscape is built precisely on this alliance: the depth, creativity, and sensitivity of human intelligence merge with the computing power, speed, and analytical capacity of AI.

From an operational standpoint, this means designing content that is truly “prompt-ready”, capable of responding not only to classic queries but also to conversational and multi-turn requests typical of Large Language Models. Text structure must be designed for interaction, dividing content into thematic sections, anticipating user questions, and offering clear, contextualized answers. LLM-compatible optimization also requires writing free of syntactic ambiguity, enriched with semantic context, and supported by structured data, such as schema.org markup. It’s crucial to pay attention to every detail: from hierarchical titles to multimedia content descriptions, to the inclusion of metadata that facilitates AI understanding and information extraction.

Another pillar of the new optimization is citation optimization: AI rewards original, well-documented content with plenty of references to authoritative sources. Citing studies, proprietary data, and official documentation not only strengthens credibility in the eyes of users, but also increases the chances of being selected and highlighted in AI Overviews and generative responses. Implementing structured data relating to authorship and citations represents an additional competitive advantage.

All this, however, is insufficient if not accompanied by constant monitoring and continuous adaptation. GEO requires an iterative approach: analyzing results, updating content based on new queries and emerging needs, experimenting with new solutions, and always being ready to react to changes in algorithms and user behavior. In this scenario, the use of advanced business intelligence, semantic analysis, and AI-driven SERP monitoring tools becomes essential.

There is a touchpoint between brands and AI in the customer journey

At TSW, we believe that true value comes from the intersection of our longstanding SEO expertise, qualitative research, and experimentation with new technologies. On these very topics, during our recent event dedicated to new brand experiences in the AI ​​era, we explored with our clients how generative linguistic models (LLMs) are becoming a new, crucial touchpoint in the customer journey. A touchpoint that, if understood and strategically managed, can profoundly impact the quality of the experience people have and the visibility of brands.

Our approach integrates listening, observation, and planning to help companies understand and leverage the narrative AI builds around their brands, and transform this new dimension of research into a competitive asset, truly focused on the best possible user experience.

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4 November 2025 Gilberto Marciano

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TAG: qualitative research SEO UX and UI digital marketing