The role of marketing communication strategy and professional expertise in AI adoption: insights from an exploratory study

Artificial intelligence (AI) is increasingly reshaping marketing by enabling firms to automate content creation, personalize communication, and predict customer behavior (Davenport et al., 2020; Huang & Rust, 2021). Although AI technologies are recognised as a fundamental component of the broader technological evolution that businesses must embrace to remain competitive (Chen et al., 2022), existing studies highlight several challenges and opportunities that must be carefully managed for effective adoption, including technological infrastructure, ethical concerns, and organizational readiness (Amin et al., 2025). Focusing on organizational readiness, the marketing literature identifies several barriers to effective AI implementation, such as high costs, lack of specialized skills, resistance to change, and difficulties in integrating AI into existing processes (Dwivedi et al., 2021; Elhajjar, 2025). However, there is still limited understanding of how firms - particularly SMEs - operationalize AI adoption in practice, especially in the domain of marketing communication. This paper aims to shed light on the role of communication strategy and professional expertise in facilitating AI adoption in marketing communication. Specifically, it presents the results of an empirical study examining the extent of AI adoption and its main applications in marketing communication among SMEs, from the perspective of marketing and communication managers. It further investigates whether the level of AI adoption intensity is associated with the presence of a communication strategy. Additionally, the study analyses how firms - grouped according to their level of AI adoption - differ in terms of marketing communication expenditure, the adoption of communication performance measurement systems, and the configuration of human resources dedicated to communication activities (i.e., in-house, outsourced, or hybrid). In this paper, AI adoption in marketing communication is not viewed merely as the implementation of a technological perspective, firms are required to develop the ability to sense emerging technological opportunities, seize them through strategic integration, and reconfigure their resource base accordingly (Teece et al., 1997; Teece, 2007). Consistent with the resource-based view, the value generated by AI in marketing communication depends on the effective combination of technological resources with complementary organizational capabilities, such as strategy and marketing expertise (Barney, 1991; Wade & Hulland, 2004). The findings indicate that SMEs characterized by the presence of a marketing communication strategy exhibit higher levels of AI adoption and firms with higher AI adoption levels tend to report greater investment in marketing communication (as a percentage of revenue), a higher incidence of communication performance measurement practices, and a more balanced configuration of communication resources between internal and external solutions. Overall, the results suggest that Italian SMEs still make relatively limited use of AI in marketing communication. At the same time, the presence of a communication strategy is associated with higher levels of AI adoption, while more advanced adoption is linked to resource configurations characterized by a stronger balance between internal capabilities and external expertise