2026-06-05T19:16:34Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/375772026-02-03T11:23:22Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Maldonado-Canca, Luis author Cabrera-Sánchez, Juan Pedro author González-Robles, Eva María author Casado-Molina, Ana María author 2024-12 The integration of artificial intelligence (AI) in marketing and business communication is transforming corporate strategies, offering significant opportunities while presenting notable challenges. This study examines the factors influencing AI adoption by companies, focusing on the perspectives of CEOs. Using a survey of 409 senior executives from Spanish firms, this research develops an advanced framework based on the unified theory of acceptance and use of technology (UTAUT), enriched with additional constructs. The findings reveal that effort expectancy and facilitating conditions are critical drivers of AI adoption. AI aversion, reflecting concerns about distrust, complexity, and ethical risks, emerges as a significant barrier, particularly for CEOs of smaller firms, where its impact is notably stronger. Relative advantage and perceived value also influence adoption intentions, albeit to a lesser degree, indicating the perceived benefits and tangible outcomes of AI in improving processes such as segmentation, automation, and predictive analytics. Key differences arise between companies of varying revenue sizes: smaller firms exhibit greater aversion to AI, whereas larger organisations focus on maximizing their strategic benefits to drive innovation. These insights highlight the importance of tailored approaches, such as financial incentives, pilot programs, and targeted training, to reduce aversion and encourage adoption across diverse organizational contexts. This study contributes to the academic discourse by extending the UTAUT framework to address emerging challenges in AI adoption. Practically, it provides actionable strategies for business leaders to address human-centric and technological barriers, fostering a more efficient and data-driven marketing process. Maldonado-Canca, L. A., Cabrera-Sánchez, J. P., Gonzalez- Robles, E. M. & Casado- Molina, A. M. (2024). AI in Marketing Management: Executive Perspectives from Companies. Marketing and Management of Innovations, 15(4), 42–55. https://doi.org/10.21272/mmi.2024. 4-04 https://hdl.handle.net/10630/37577 10.21272/mmi.2024.4-04 Gestión de marketing AI in Marketing Management: Executive Perspectives from Companies.