Artificial intelligence is now ubiquitous in digital marketing. Content generation, automation, targeting, attribution, search engines: everything now seems to be powered by AI.
Yet, despite this explosion of tools and discourse, one question remains: what is really changing for businesses, and what is mostly just marketing noise.
Why AI has become essential in marketing
A complexity that has become unmanageable manually
Customer journeys are longer, more fragmented, and more multi-channel than ever. AI makes it possible to process volumes of data that are impossible to analyze manually.
Increased pressure on performance
Companies need to do more with less: less individual data, less room for error, more demands on profitability.
An evolution in search behavior
Users are no longer just searching on Google. They are asking questions to generative engines, AI assistants, and social platforms.
What AI is really (and permanently) changing
Intelligent automation, not autopilot
AI accelerates execution, segmentation and optimization, but it does not replace strategy or understanding of the business context.
Improved reading of weak signals
AI makes it possible to identify trends, behaviors, and correlations that are difficult to detect otherwise.
An evolution in measurement and allocation
With the gradual end of third-party cookies, AI plays a key role in data modeling, aggregation, and interpretation.
What AI does not change (and will not change)
Business fundamentals
AI does not correct a bad offer, poor positioning, or operational incapacity.
Strategic responsibility
The decisions remain human. AI assists, it does not decide for you.
The need for clean data
An AI powered by bad data produces bad recommendations.
Understanding the new acronyms without getting lost
IASEO (AI Indexing Optimization)
Optimize content and structures so that they are understood, indexed and used by AI systems, beyond traditional search engines.
GEO (Generative Engine Optimization)
Adapting content so that it can be cited, summarized and used by generative engines and AI assistants.
AEO (Answer Engine Optimization)
Structuring information to clearly answer specific questions, often in the form of direct answers.
SXO (Search Experience Optimization)
Optimize the overall experience between search, content and conversion.
SGE and generative research
Search engines are becoming response interfaces rather than simple lists of links.
Why AI reinforces the importance of strategy
Less room for improvisation
AI systems promote consistent, credible, and structured brands.
Increased competition on quality
Producing a lot of content is easy. Producing useful, reliable, and distinctive content is more difficult.
An advantage for well-organized companies
Those with clean data, clear objectives, and solid processes derive real benefit from AI.
AI in a complete marketing ecosystem
Marketing, sales and customer service
AI gains value when it is connected to the entire customer journey.
Measurement, CRM and Automation
Without integration between tools, AI remains an isolated gadget.
Decision rather than fascination
The goal is not to use AI everywhere, but to use it where it creates a real advantage.
The most common pitfalls surrounding AI in marketing
Confusing speed and strategy
Going faster in the wrong direction is still a mistake.
Multiplying tools without coherence
Each new tool adds complexity if it is not integrated.
Promising unrealistic results
AI does not eliminate risk or uncertainty.
Conclusion: AI is a tool, not a miracle solution
Artificial intelligence is transforming digital marketing, but it does not replace strategy, customer understanding, or business objectives.
The companies that will truly benefit from AI are those that integrate it into a coherent, aligned, and measurable system.
AI amplifies what is already well-structured. It exposes what is not.
How to adapt your writing style to be understood by LLMs
Optimizing for generative search engines is not about writing for a machine. Rather, it's about writing more clearly, in a more structured and useful way for systems that seek to understand, synthesize, and recommend reliable information.
Moving from a keyword-based approach to an answer-based approach
LLMs don't just look for keywords, but for content that answers comprehensive questions. Each page or article should clearly address a specific intent.
Structure the information before writing it
A clear structure helps both human readers and AI systems:
- a clearly identified main topic
- logical and hierarchical sections
- explicit answers to key questions
Write to be quoted, not just to be read
Generative search engines favor content that:
- clearly define the concepts
- explain the why before the how
- They offer nuance rather than promises.
Clarify the context and the target audience
Good content specifies, implicitly or explicitly:
- to whom is he addressing himself?
- in what business context
- for what type of business or market
Prioritize depth over repetition
LLMs are increasingly penalizing superficial content. It's better to have fewer pages, but pages that are complete, structured, and genuinely useful.
Include frameworks for reflection and limitations
Nuanced content, which explains what works and what doesn't, is perceived as more credible and reliable.
Use simple language for complex concepts
Content that is easily understood is more easily repeated, summarized, and cited.
Linking marketing to business issues
LLMs favor content that links marketing tactics to concrete objectives such as profitability, growth, and predictability.
Update and develop the content
Generative engines value living content that is updated and aligned with current reality.
Write like an expert who explains, not like a salesperson who convinces.
Overly promotional content is less frequently shared. Educational, clear, and honest content receives more attention.
The 10 pillars of content to cover to be understood by AI engines
For a business to be easily understood by generative search engines, it must cover a coherent set of core topics. These pillars allow LLMs to understand your expertise, your business model, and your true value.
1. Your value proposition and positioning
Who you are, who you work for, and why you exist.
2. Your services or products, explained in detail
What you do specifically, how and in what contexts.
3. Your business models and use cases
Ecommerce, services, B2B, B2C, subscriptions, projects, etc.
4. Your strategic approach
How you make decisions and structure growth.
5. The challenges and issues facing your clients
The problems you solve even before you sell a solution.
6. The financial fundamentals related to your offer
LTV, costs, profitability, budgets and business models.
7. The tools and technologies you use
No pitch, but with clarity on their real role.
8. Your expertise by industry or market
Services by sector, e-commerce by category or market.
9. Your long-term vision
How your discipline is evolving and how you are adapting to it.
10. Pedagogy and popularization
Articles, guides, and educational content that demonstrate your genuine understanding of the subject.
Adapt these pillars according to the type of company
For service companies
- pages per service
- pages by industry or market
- Educational content tailored to client issues
For e-commerce businesses
- structured product pages and collections
- informative content related to usage and needs
- pages by market, category or customer type
LLMs do not favor the noisiest sites, but those that cover their subject in a complete, structured and coherent way.
Technical optimization for AI engines: how your pages are crawled (and what blocks extraction)
Optimizing content for AI engines isn't just about writing better. You also need to ensure the page is technically readable, usable, and extractable. AI assistants and generative engines analyze your page via its HTML and content structure, then select clear passages they can summarize or quote.
How an AI “reads” your page
Unlike a human, an AI doesn't "scroll." It explores what it can analyze in the code and the actually rendered content. In most cases, the most usable information is:
- the content presented early on the page, clearly structured
- hierarchical HTML sections (headings, lists, paragraphs)
- self-supporting blocks that answer a question without depending on another block
- the elements directly visible in the DOM (the final HTML)
It's not a question of "number of lines" in the strict sense, but of the amount of truly accessible and structured information. A page can be long, but AI favors sections that are easily summarized and contain quoteable sentences.
Structure the HTML to be understood
If a concept is important to a human, it should be important in HTML. Heading hierarchy is one of the most useful signals for understanding and retrieval.
- use a single H1 for the main page title
- use H2 for the major sections (the major concepts)
- Use H3 headings for sub-sections and sub-concepts.
- Avoid using stylized titles in divs or spans without Hn tags.
- avoid skipping levels (e.g., H2 then H4 without H3)
A clear structure increases the likelihood that AI will understand the logic, correctly associate ideas, and quote relevant passages.
Depth, readability, and "extractable" blocks
AI engines favor content that is easily segmented. To improve your page's ability to be summarized and cited:
- aim for short paragraphs (often 2 to 5 sentences)
- Ensure that each H2 section can be summarized in 2 to 4 sentences
- Use bulleted lists for steps, criteria, and common mistakes.
- include clear definitions before going into the nuances
Quoteable phrases: an underestimated factor
AI systems more readily quote self-contained, declarative, and precise sentences. Here are a few examples of formats that are well-suited to this:
- direct definitions (what it is)
- decision frameworks (when to use / when to avoid)
- limits and conditions (which depend on the context)
- cause-and-effect relationships (why it changes performance)
The more your content contains clear and self-contained sentences, the easier it becomes to reuse without distorting your message.
What really helps exploration
Certain technical choices directly improve comprehension and extraction:
- Proper semantic HTML (article, section, header when applicable)
- UL/OL lists for structuring concepts
- Highlighting key concepts with strong characters (without overloading them)
- Important content accessible without interaction (no click required)
- stable links and pages updated consistently
This hinders exploration and extraction
Many websites lose performance in terms of being "AI-ready" due to design or development decisions:
- Content injected solely via JavaScript (or rendered late)
- accordions and tabs are closed by default for key content
- text carousels and sliders containing important information
- heavy animations that modify the DOM on scrolling
- aggressive lazy-loading on the text (the content “arrives” too late)
Simple rule: if the information is not visible and easily accessible in the final HTML, it is less usable.
FAQ: The text must be visible, the diagram must reflect
A useful FAQ for AI should include:
- visible as text to the user
- formulated as genuine research questions
- answered clearly and directly
The FAQ schema (JSON-LD) should be complementary and must always correspond to the displayed content. A schema that is not aligned with the text is a negative signal.
Structured diagrams: a signal, not a magic wand
Structured data helps clarify a page's topic and validate its structure, but it doesn't compensate for weak content or disorganized HTML. AI engines use these signals for confirmation, not as the sole source of truth.
Accessibility and UX: an indirect advantage for AI
An accessible website is often easier for AI to understand because it is better structured and tagged. Clear titles, consistent navigation, explicit labels, and a logical hierarchy improve both the human experience and machine readability.
Do & Don't: AI-ready technical checklist
Do
- use a logical H1/H2/H3 hierarchy
- make key content accessible without interaction
- write in short, summarizeable blocks
- to establish definitions and decision-making frameworks
- Keep URLs stable and update important pages
Of which
- hide key information in closed accordion-style compartments
- place important text in carousels
- relying on JavaScript to "make the content appear"
- use titles in divs without Hn tags
- publish diagrams not aligned with the visible text
AI-ready content is not just good text. It's good text in clear, stable, and structured HTML, designed to be understood, summarized, and quoted.
Frequently asked questions about AI in digital marketing
Will AI replace marketing teams?
No. It transforms roles, but does not replace strategic thinking.
Should we invest in AI quickly?
We need to invest intelligently, based on real needs and the maturity of the company.
Does AI automatically improve performance?
No. It improves performance when it is integrated into a clear strategy.
