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EU: AI and direct marketing

In today's digital age, businesses are constantly seeking innovative ways to connect with their customers and drive growth. One technology that has been making waves in the marketing industry is artificial intelligence (AI). According to the definition laid down in the EU AI Act in the last version available, 'AI system' means 'a machine-based system designed to operate with varying levels of autonomy, that may exhibit adaptiveness after deployment and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.' Gianluigi Marino and Andrea Cantore, from Osborne Clarke, define AI in marketing and discuss risks and obligations.

Delmaine Donson/E+ via Getty Images

Defining AI in marketing

Before delving into the applications of AI in marketing, it is important to understand what AI encompasses. AI can be classified into various types, including marketing automation, machine learning (ML), natural language processing, voice search, virtual assistants, and chatbots. These technologies enable businesses to automate processes, analyze vast amounts of data, and make data-driven decisions.

AI and decisions for marketing purposes

One of the key areas where AI is transforming marketing is in the analytical phase. AI-powered solutions, such as text and Big Data analysis, sentiment analysis, and predictive analytics, provide valuable insights into customer behavior. By identifying specific customer behaviors and predicting their needs, businesses can segment their audience effectively and develop targeted marketing strategies. For example, platforms can utilize ML algorithms to optimize advertising campaigns and target users who are more likely to make a purchase.

AI and customer relationship management

AI is also revolutionizing customer relationship management (CRM). Virtual assistants, interactive voice response systems, and chatbots are examples of AI applications in CRM. These tools enable businesses to automate customer interactions and provide personalized support. Additionally, AI can be used to develop predictive models for effective churn management, identifying customers who are likely to switch to a competitor's product or service.

AI is already used for a number of different applications. Dynamic pricing, advanced advertising targeting, email marketing automation, creation of personalized website experiences, and automated content creation are all examples of how AI can be used to deliver personalized offers and enhance customer engagement.

Predictive analysis: unlocking customer insights

One of the most powerful applications of AI in marketing is predictive analysis. By leveraging past customer actions and purchase habits, businesses can group customers into common clusters and predict their future behavior. These valuable behavioral patterns can be used to develop effective marketing strategies.

Risks associated with AI in marketing

While AI offers numerous benefits, there are also risks associated with its use in marketing. These include:

  • Interpretation challenges: As the volume of data collected from various sources continues to grow, interpreting and utilizing this data effectively becomes increasingly difficult. This can hinder the evaluation of marketing campaigns' effectiveness and optimization processes.
  • Technological issues: Lack of necessary technological expertise within an organization can lead to infrastructure and operational challenges, impacting the performance of AI systems.
  • Security concerns: Before implementing AI in marketing, it is essential to prioritize security measures to safeguard customer information, identity, and rights of the data subject/consumer.
  • Cognitive bias: Cognitive bias refers to unconscious biases present in the data used to train algorithms. These biases can arise during data selection or during the training stage, or they might be caused by cultural and social factors influencing data collection. To mitigate this bias, businesses must include a wide range of information and continuously monitor algorithmic decisions to ensure fairness and effectiveness in marketing activities.

Transparency obligations

Article 50 of the AI Act outlines transparency obligations for providers and deployers of certain AI systems. Providers shall ensure that AI systems intended to interact directly with natural persons are designed and developed in such a way that the natural persons concerned are informed that they are interacting with an AI system, unless this is obvious from the point of view of a natural person who is reasonably well-informed, observant, and circumspect, taking into account the circumstances and the context of use.

Deployers of an emotion recognition system or a biometric categorization system shall inform the natural persons exposed thereto of the operation of the system, and shall process the personal data in accordance with the General Data Protection Regulation (GDPR), as applicable.

Deployers of an AI system that generates or manipulates image, audio, or video content constituting a deep fake, shall disclose that the content has been artificially generated or manipulated. This might be relevant where the content created with the AI is used for marketing purposes.

The information above shall be provided to the natural persons concerned in a clear and distinguishable manner at the latest at the time of the first interaction or exposure. The information shall conform to the applicable accessibility requirements.

Long story short, it shall be key not only to identify when transparency obligations will be relevant in the context of marketing (in particular, direct marketing) and advertising but also how to concretely put them in practice (waiting for possible codes of practice encouraged and facilitated by the AI Office).

In any case, the general principle regarding fairness vis-a-vis consumers (e.g., unfair commercial practice directive and the Digital Services Act (DSA)) will still apply and, more importantly, are already applicable before the enter into force of the AI Act. This is particularly true with reference to so-called 'dark patterns,' namely those practices that materially distort or impair, either on purpose or in effect, the ability of recipients of the service to make autonomous and informed choices or decisions. Despite that 'dark pattern' is only mentioned in the DSA, they might in any case fall under the umbrella of the unfair commercial practices directive.

While personalization is a key benefit of AI in marketing, data protection regulations must be taken into account and data protection regulatory authority should have already enforced the GDPR with reference to AI solutions.

If the usage of AI systems triggers the processing of personal data, businesses must comply with the GDPR. A thorough due diligence regarding which data has been used for training the AI is a first step which could be useful not only to address GDPR compliance issues but also to mitigate the risk of possible intellectual property infringements.

Transparency requirements need to be addressed under Article 13 of the GDPR. How to concretely comply with transparency requirements from a data protection standpoint but also consumer protection standpoint will not be easy at all. Moreover, these layers of transparency requirements shall be supplemented by the AI Act (and also by the Data Act in the framework of the Internet of Things (IoT) environment).

To the extent that the AI systems will play a key role in the decision-making process, compliance with Article 22 of the AI Act shall be addressed. On one hand, businesses shall grant the explainability of decisions, on the other hand, businesses shall be aware that introducing these tools might likely result in additional rights on the data subjects. Businesses' staff should also be trained in respect of this aspect.


In conclusion, AI is revolutionizing the marketing landscape, enabling businesses to automate processes, gain valuable customer insights, and deliver personalized experiences. However, it is crucial for businesses to navigate the challenges associated with AI implementation, such as interpretation difficulties, technological issues, security concerns, and cognitive bias. The adoption of AI systems should be carefully assessed from many different points of view without just being dazzled by the 'magic' and velocity of these new tools.

By embracing AI responsibly and maintaining transparency, businesses can harness its potential to drive growth and enhance customer relationships mitigating the regulatory and legal risks.

Gianluigi Marino Partner
[email protected]
Andrea Cantore Lawyer
[email protected]
Osborne Clarke, Milan