In July 2026, a group of major international publishers — including Hachette, Cengage, and Elsevier — filed a new lawsuit against Google. The accusation concerns the use of copyrighted works to train artificial intelligence models, without the necessary authorizations. This is yet another chapter in a legal dispute involving the main players in generative AI.
However, the scope of this matter extends far beyond the courtroom. In fact, the implications extend directly to the content marketing strategies and martech platforms that Italian companies use every day. Consequently, marketing managers and digital leads must begin to consider the regulatory exposure of their tech stacks. In particular, the use of AI tools for content production could be subject to significant revisions in the coming months.
At SHM Studio, we closely monitor the evolution of this regulatory landscape. Therefore, in this article, we offer a strategic reading of the situation, focusing on the operational implications for those managing content strategy, SEO, and digital campaigns in Italy. Finally, we propose some concrete recommendations for navigating an ever-evolving scenario.
The timeline: from OpenAI to Google, an expanding legal front
On July 14, 2026, TechCrunch reported a new class action lawsuit against Google. The plaintiffs include heavyweights in academic and commercial publishing: Hachette, Cengage, Elsevier, and other internationally renowned publishers. The accusation is direct: Google allegedly used copyrighted works to train its artificial intelligence models without obtaining the necessary licenses.
This is not an isolated case. In fact, over the past two years, the landscape of legal disputes surrounding generative AI has rapidly intensified. OpenAI has faced lawsuits from The New York Times and other publishers. Stability AI was cited by Getty Images. Similarly, Meta and other big tech companies are dealing with similar proceedings in different jurisdictions. Therefore, the lawsuit against Google fits into a structural pattern, not an exceptional episode.
What distinguishes this proceeding is the quality of the plaintiffs. Elsevier, in particular, is one of the world's leading distributors of scientific and academic content. Cengage operates in the educational publishing market. Hachette is among the big five global trade publishers. Consequently, the economic and symbolic value of the works involved is considerable.
The legal knot: fair use or systematic appropriation?
The heart of the dispute revolves around the doctrine of Fair use, a cornerstone of U.S. copyright law. Google, like other AI developers, argues that training on publicly accessible data constitutes fair use. Publishers, conversely, contend that the massive ingestion of copyrighted works to build commercial products cannot qualify as fair use.
The issue is far from settled. However, some recent rulings are beginning to outline jurisprudential trends. The Verge has documented how the NYT vs. OpenAI case is setting important precedents. Furthermore, the European Union has already introduced transparency obligations regarding training data into the AI Act, with direct implications for models distributed in Europe.
Therefore, for companies operating in Italy, the regulatory framework is not solely American. In fact, European regulations tend to be more restrictive regarding intellectual property and data processing. Consequently, the evolution of these procedures will also have concrete repercussions on AI tools adopted in the Italian market.
Winners, losers, and those who watch from the window
A strategic reading of the situation requires identifying who stands to gain and who stands to lose in this scenario. Publishers, of course, aim to obtain financial compensation and, above all, to establish a licensing model for the use of their content in AI training. In this regard, they could be the long-term winners, if the courts rule in their favor.
Google, for its part, has the legal and financial resources to resist for a long time. However, a loss in court could force it to renegotiate access to training data for Gemini and other models in the Google AI family. Consequently, the development and maintenance costs for these systems could increase significantly.
Those observing with interest are alternative providers of AI-ready content, licensing platforms, and ethically curated data marketplaces. Furthermore, opportunities are emerging for those developing models trained on datasets with explicit licenses — a segment that could grow rapidly in the next 18-24 months. Finally, end-users — namely companies integrating AI into their marketing workflows — find themselves in a forced waiting position.
SHM Studio's Reading: Three Implications for Italian Martech
We of SHM Studio We work daily with marketing managers and digital leaders from Italian SMEs and mid-market companies. Therefore, we have identified three concrete implications that this situation entails for those who manage martech stacks and content strategies.
First implication: the origin of training data becomes a criterion for vendor selection. Until yesterday, few marketing managers were concerned with knowing what data the AI model they used was trained on. Following these legal developments, this question will become an integral part of technology procurement processes. Similar to what is already happening with GDPR for personal data, increased attention is expected on data provenance in AI vendor contracts.
Second implication: AI-generated content may be subject to policy revisions. If courts were to rule that certain models infringed copyright, platforms could be forced to modify or withdraw features. Consequently, those who have built content production workflows entirely dependent on a single AI tool would find themselves exposed. Therefore, diversifying tools and maintaining in-house editorial expertise remains a sound strategic choice.
Third implication: the value of the original content is re-evaluated. Paradoxically, this wave of legal disputes strengthens the positioning of those who produce authentic content based on proprietary expertise. In fact, search engines—including Google—are already signaling a preference for content with strong signals of authority and originality. Therefore, investing in Strategic copywriting and in a SEO Orienting towards E-E-A-T is not just a good practice: it's a form of competitive resilience.
The impact on digital marketing platforms
The repercussions of these legal proceedings do not only concern content creators. In fact, they also involve the platforms through which content is distributed and amplified. Google Ads, for example, is increasingly integrating generative AI features—from automatic asset creation to Performance Max campaigns. Similarly, LinkedIn has introduced AI tools for generating ad copy.
If the models underlying these features were subject to legal restrictions, platforms could be forced to limit or modify such features. Consequently, the teams managing Google Ads campaigns o LinkedIn campaign they should carefully monitor any official communications from their respective providers.
In addition to this, the theme is intertwined with the management of AI services integrated into the workflows of digital marketing. Therefore, it is advisable to start documenting which AI tools are being used, for what purposes, and with what frequency—also with a view to future compliance audits.
What no one tells you: the content problem
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