Digital marketing in 2026 is no longer guided by the same benchmarks as it was twelve months ago. The implementation of entire sections of the European AI Act, the rise of GEO (Generative Engine Optimization), and the reshaping of purchasing journeys around non-Google sources are changing operational decisions. Here, we detail the areas that are concretely altering the way campaigns are produced, disseminated, and measured.
AI Act and AI-generated advertising: the new European regulatory framework
Since August 2, 2026, Regulation (EU) 2024/1689 imposes two levels of transparency on advertising content produced or manipulated by artificial intelligence. The tool provider must integrate a machine-readable label directly into the file. The advertiser or publisher, on their part, must include a visible mention from the first contact when the visual constitutes a hyper-manipulation, meaning it sufficiently resembles real people, places, or events to be taken as authentic.
Classic retouching (background removal, color adjustments) and marketing texts generated by AI without claims of factual accuracy do not fall under this obligation. This distinction creates an area of editorial responsibility that each team must document internally. We recommend maintaining a register qualifying each asset according to its level of manipulation, even before dissemination.
For advertisers working with specialized agencies, it becomes necessary to discover Media Markéting online to verify the compliance processes implemented on the provider’s side. Non-compliance with these obligations exposes one to graduated sanctions provided by the regulation.
GEO and visibility in generative engines
Traditional SEO is no longer sufficient to capture qualified traffic. Responses generated by SearchGPT and Google AI Overview absorb an increasing share of informational queries. Optimizing for these interfaces requires a change in methodology.
GEO (Generative Engine Optimization) is based on one principle: generative engines select the sources they cite based on factual density, data structuring, and domain reputation. Vague or purely editorial content is unlikely to be picked up. Content structured around verifiable data, with named entities and comparative tables, increases its chances of appearing in synthesized responses.
Operational criteria for GEO
- Structure each page around a precise search intent, avoiding catch-all content that dilutes the thematic signal
- Integrate structured data (schema.org) on entities, FAQs, and reviews to facilitate automated extraction
- Enhance domain authority through citations on comparison sites and trusted third-party sources, as generative engines weigh editorial reputation in their source selection
Monitoring the developments of Google AI Overview remains necessary: the criteria for selecting cited sources change with each major update.
First-party data strategy and gradual end of third-party cookies
The announced disappearance of third-party cookies reshuffles the cards of advertising targeting. Companies that have not yet structured their collection of first-party data lose in personalization capacity and media profitability.
Specifically, first-party data comes from direct interactions: forms, purchase histories, on-site behaviors, CRM data. It feeds proprietary segmentation models and allows for the construction of similar audiences without relying on third parties. The issue is not only technical: it engages the trust relationship between the brand and its users.
Concrete activation
Customer Data Platform (CDP) solutions allow for the unification of these sources in real-time. The major interest lies in the ability to personalize journeys without resorting to external identifiers. Campaigns fueled by proprietary data generally show better engagement and conversion performance than those based on generic third-party segments.
Documenting consent at each point of collection remains an obligation under GDPR, and the DSA strengthens transparency requirements for targeted advertising disseminated via very large platforms.
Expert and embodied content in the face of AI saturation
The proliferation of AI-generated content creates a saturation effect on organic channels. Brands that stand out in 2026 are betting on content authored by identified experts, with a clear editorial line.
Employee advocacy (employees speaking on their professional networks) and long-form content delivered by a recognized author in their field generate higher engagement than anonymous content. Google’s E-E-A-T signal (Experience, Expertise, Authoritativeness, Trustworthiness) explicitly values field experience and the author’s identity.
Preferred formats
- Technical articles signed with a verifiable biography, which enhance the credibility of the domain with both engines and readers
- Short videos shot in real conditions (behind the scenes, demonstrations, field feedback) rather than smooth corporate productions
- Newsletters segmented by level of expertise, which nourish the direct relationship and escape the algorithmic fluctuations of social platforms
The marketing loop replaces one-shot campaigns: each published piece of content feeds a reuse cycle (video excerpt, LinkedIn post, newsletter entry) that increases the return on editorial investment without additional production.
Budgetary arbitration shifts: less volume, more depth. Companies producing three expert pieces of content per month gain more organic traction than those publishing generic texts daily. The editorial strategy becomes a measurable differentiation lever, provided results are documented and iterations are based on real data rather than intuitions.
