Under pressure from the rapid deployment of AI, Tech marketing departments risk drowning their expertise in the production of ever more standardized content.
The Tech sector is experiencing a contradictory injunction. On the one hand, the entire ecosystem expects software publishers and ESNs to be, almost by magic, mature in the use ofArtificial intelligence. General management is demanding six-month roadmaps with quantified productivity gains. B2B buyers (DSI, CTO) are already using AI to compare complex solutions, forcing us to explore new areas such as GEO (Generative Engine Optimization).
On the other hand, this pressure pushes marketing teams to multiply initiatives and tests in a disorderly manner. But if AI today gives any employee the ability to produce marketing actions at high speed, it does not give the ability to produce a fair, differentiating message aligned with the company’s strategy.
The mirage of the shared prompt and the advent of Marketing chaos
We need to get rid of a stubborn fantasy: just because a marketing department shares a library of fifty prompts doesn’t mean its teams are aligned.
Under the pressure of urgency, autonomy often progresses faster than coordination. We are thus seeing Shadow Marketing situations multiply: technical experts who generate twenty completely slick blog articles in their corner, salespeople who invent themselves as marketers on LinkedIn with dissonant arguments, or juniors who provide visuals that no longer respect any identity code. AI scales speech that, if left unchecked, becomes average (at best), incoherent (often), unproven, and ultimately invisible.
At a time when Google is massively deindexing commodity content (this content without added value found everywhere else) and where social network algorithms penalize publications 100% generated by AI, producing “more” no longer serves any purpose if we do not produce “different”. It’s no longer an operational risk, it’s a brand risk.
Context Engineering: the lesson for development teams
To find the solution, let’s look at the technical teams who have been experiencing this shift for longer, particularly among developers. Today, a massive part of the code is proposed by AI, under human control. No one would imagine saying: “Every developer can generate code with their own framework and architecture in their own corner”. This is where the strategic role of Lead Dev and Context Engineering comes in: consolidating standards and architecture at the company level.
Marketing is going through exactly the same transformation, and our context can no longer be managed individually. Our brand platform, our editorial charter, our elements of differentiation and our proofs must no longer sleep in PDFs designed for a human eye. They must be translated into material that can be used by the machine.
Making your brand AI-Ready: from theory to industrialization
How do we go from a classic charter to an AI-Ready base? Take the example of visual identity. Asking an AI to produce a “dynamic, modern and premium” image (the classic vocabulary of our graphic charters) will only produce random results. The AI needs a dictionary of technical keywords: type of lighting, focal length, image grain, 3D processing, framing. You have to isolate assets (like a brand mascot or key graphic elements) and train the AI on these specific models.
The same goes for the production of texts. An editorial guideline that places all its tone sliders “in the middle” will produce generic content. Strict behavioral instructions must be defined: technical level, prohibited words, systematic use of anecdotes or proof by example.
The objective is to industrialize this approach via semantic knowledge bases, or even Generative Brand Books, dynamic collaborative spaces which guarantee absolute consistency of queries, regardless of the user.
GEO and incarnation: the human expert more essential than ever
Getting your house in order is only the first part of the process. The second concerns our external visibility. Generative AIs now decode your brand’s overall footprint. To exist in this new GEO paradigm, the uniqueness of the brand is no longer enough: strong external signals, embodied by real experts, are needed.
It would be tempting to use AI to create fake profiles that would flood networks of interest to the IT sector, such as Reddit. But just as SEO ended up severely penalizing keyword stuffing, AI will increasingly value authenticity (Google’s famous EEAT) and coherence of the “Author” entity.
Restricting your technical experts, consultants or product managers is therefore not the solution. On the contrary, they must be activated. But not by forcing the line. The right approach is based on a precise mapping of their current presence perceived by the AI (often rich in lessons and quick-wins that are rewarding for them) and on a mutual commitment around targeted actions. Nothing is more effective in transforming an expert into an ambassador than proving to them that one of their authentic speaking engagements generated a qualified lead.
Succeeding in this AI-augmented shift goes beyond the sole coherence of the marketing department. The real challenge is to guarantee that all production, communications and external signals remain perfectly aligned with the brand’s identity and its real expertise, whether they are generated by marketing, sales or technical teams. It’s about limiting dissonance while accelerating the pace. This exercise requires an unprecedented combination of skills: combining real business expertise (artistic direction, B2B editorialist), a transversal strategic vision and technological mastery of AI. If the tool is the essential lever for this acceleration, the compass which ensures this global coherence remains profoundly human.
