Organisatoriska och strategiska beslut om AI i B2B-marknadsföring

Artificial intelligence (AI) is frequently described as a strategic resource for marketing, yet empirical insights into how AI is adopted and used in business-to-business (B2B) marketing remain limited. Prior research has predominantly focused on technological capabilities or consumer-oriented contexts, while organizational and strategic considerations in B2B firms have received less attention. This study addresses this gap by examining which organizational and strategic factors influence B2B companies’ decisions to implement, limit, or postpone the use of AI in marketing. The study applies a qualitative, comparative case study design involving three Swedish B2B companies with varying levels of AI maturity. Empirical data were collected through nine semi-structured interviews with respondents in strategic and operational roles within marketing, digital development, and IT. An abductive analytical approach was applied, integrating the Technology-Organization-Environment (TOE) framework and Diffusion of Innovation (DOI) theory to examine both structural conditions and adoption dynamics. The findings indicate that AI is primarily used as an operational support tool aimed at efficiency gains rather than as a strategic driver of marketing activities. This pattern is not explained by limited technological availability, but rather by organizational factors such as unclear strategic ownership, constrained resources, limited analytical competence, and challenges in demonstrating long-term business value. From a DOI perspective, AI is perceived to offer clear relative advantages in terms of automation and time savings, while the observability of strategic outcomes remains low. Consequently, organizations prioritize use cases with immediate and measurable benefits, reinforcing a cautious and incremental adoption process. By integrating TOE and DOI, the study contributes to a more nuanced understanding of AI adoption in B2B marketing. The results suggest that AI adoption should be understood primarily as an organizational and strategic maturity issue rather than a technological one, and that limited or