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Technological advancements, particularly in generative Artificial Intelligence (AI), arenowadays transforming industries globally. Generative AI, by leveraging automated andadaptive solutions, offers significant potential for minimizing human intervention invarious tasks. This capability introduces transformative applications in Marketing,where the integration of AI allows for enhanced productivity and strategic insights.

Generative AI can help in absorbing and performing tasks involving data and cantherefore have an impact over numerous Marketing activities: macro and microenvironmental analyses; segmenting, targeting and positioning; planning direction andobjectives; developing product features; setting product prices; improving logistics;determining influence strategies; as well as planning metrics and implementationcontrol. Generative AI can thus provide additional valuable insights about theconsumers’ preferences or needs but also automate and engage throughcustomer-relationship management tasks. So generative AI can be implemented in everypart of the Marketing function, from the product prototyping phase to after-salesservices. Consequently, it enables Marketing employees to shorten time-consumingtasks in favor of greater productivity.

Despite highlighting all the benefits of using generative AI in gaining efficiency andefficacy in Marketing, one must not forget, as literature shows it, about the criticalnuanced roles that human Marketing employees play, particularly in tasks requiringsensitivity, creativity, wisdom, judgment and contextual understanding. Indeed, Marketing does not only rely on data, but also includes activities that require humanunique inputs and skills. Generative AIs remain hardware tools transforming data intoinformation. But this information needs to be evaluated through human factors such asintuition, expertise, past experiences and soft skills of the Marketing professionals tobecome exploitable knowledge and drive towards successful Marketing strategies. As amatter of fact, the insights provided by humans are critical factors that cannot begenerated by AI, at least today.

The key to successful Marketing strategies in the future is thus to effectively combinehuman insights with generative AI tools. However, such a powerful combinationrequires a high level of collaboration between the two entities, which is not yet the casedue to numerous issues among which reliability, interpretability, and trust. Thisenhanced collaboration, called hybrid intelligence, is thus what the Marketing functioncould aim for, but it is not there yet.

That is why through this thesis, we aimed at illustrating how the key to successfulMarketing applications and strategies is to find the adequate combination betweenautomated data processing and human subjectivity, and to lead a reflection on how to doso through an enhanced collaboration between generative AIs and humans working inthe Marketing function. To get there, we also searched and explored how a key elementsuch as trust, is an influencing factor for the relationship between the two entities.