AI appeals to marketing, but its complexity is confusing. In 2024, 67% of companies have already integrated it; 82% for large ones. The challenge: choose the right tools strategically.
Artificial intelligence (AI) is generating real excitement in the field of marketing, but the abundance and complexity of the solutions available can quickly discourage advertisers. While AI can significantly improve the effectiveness of campaigns and generate measurable results, you still need to choose the right tools. By 2024, more than 67% of companies in Europe say they have integrated at least one AI-based tool into their marketing or sales processes – a figure that rises to 82% among large companies. This massive adoption highlights the urgency of adopting a strategic and selective approach.
Implement a successful AI strategy
Any effective AI implementation begins with a rigorous audit of existing practices and infrastructure. It is about identifying areas in which AI can really bring added value, beyond fads. In a context where marketing professionals must demonstrate the concrete impact of their actions, it is crucial to precisely measure the efficiency gains and savings generated by these new technologies.
But the issue is not limited to performance evaluation. Today, the increasing complexity of campaigns – between multiple audiences, varied formats, heterogeneous platforms, precise timing, creative requirements and advanced targeting – far exceeds the human capacity to make rapid and relevant decisions. AI solutions integrated into platforms offer an answer in terms of responsiveness, but often at the expense of transparency and control. Hence the growing importance of Applied AI tools, which give marketing teams a clear strategic vision and allow them to act proactively, rather than simply reactively.
Valuing proprietary data
Combined with robust cloud platforms, this data not only provides the scalability and security essential in today’s digital environment, but also unlocks access to enterprise-grade artificial intelligence capabilities. Companies can thus activate all their data and cloud potential to deploy efficient, secure and scalable AI models. This approach, already adopted by the most advanced players, makes it possible to reconcile technological innovation and governance requirements, by transforming proprietary data into real strategic levers.
Meeting the challenge of creative fatigue
Furthermore, an increasingly pressing challenge for brands is that of “creative fatigue”: audience saturation with repetitive content, which leads to a drop in engagement. However, creative assets can represent up to 50% of a campaign’s performance, but they often remain static, rarely updated in real time. Performance-oriented AI makes the difference here. Performance-oriented AI provides a direct answer to this problem. Thanks to generative models connected to performance data via APIs and integrated into scalable cloud environments, it becomes possible to automatically produce and adjust thousands of creative variations. Content is tested, deployed and optimized continuously according to signals received from media platforms and audience behavior.
With dynamic creative optimization (DCO) driven by AI, messages are personalized in real time according to the profile, interaction history or detected intention. Concretely, this means less advertising saturation, more relevance in each point of contact and ultimately, a measurable improvement in creative and media ROI.
Predictive AI for anticipation and efficiency
Predictive analysis, powered by AI, is another powerful lever for anticipating behavior and optimizing marketing operations. By exploiting historical data, predictive models make it possible to better segment audiences, refine advertising investments and improve inventory management. These approaches maximize return on investment. A recent study reveals that a euro invested in generative AI returns on average €3.7 and up to €10.3 for companies most advanced in their adoption.
Regain confidence and mastery with applied AI
In an environment where automated platforms often operate as “black boxes”, applied AI tools provide a beneficial response. They offer marketers clear analyses, precise insights into the most effective creative combinations and allow them to regain control over performance levers. Companies no longer suffer from algorithms: they use them strategically. According to the European Observatory of AI Applied to Marketing, 42% of European companies having invested in these technologies say they have seen a positive ROI from the first year, particularly on acquisition and loyalty campaigns.
AI Agents: towards autonomous and proactive marketing
The emergence of AI Agents marks a new stage in the evolution of digital marketing. Unlike traditional models, these intelligent agents are not limited to analyzing or generating content: they interact autonomously with the marketing ecosystem. Connected to advertising platforms, CRM and analytics tools via API, they are capable of orchestrating end-to-end campaigns — from media activation to creative optimization. This translates into a major gain in responsiveness and operational efficiency for companies. AI Agents can continuously test different bidding strategies, adjust budgets based on real-time performance or even trigger targeted actions based on specific signals (purchase intention, potential loss of a customer, cross-sell opportunity). By automating these complex and time-consuming tasks, they free up marketing teams to focus on strategy and innovation, while maximizing ROI and campaign relevance.
Conclusion: make AI a strategic lever, not just technological
Ultimately, AI adoption should not be limited to a technology race. It involves real strategic thinking. By auditing their practices, leveraging their proprietary data and intelligently integrating applied AI into their marketing processes, companies can transform the theoretical potential of AI into concrete performance – while reaffirming their mastery and confidence in a constantly evolving digital environment.
