Enabling Marketing Capabilities through Artificial Intelligence: A Multi-Case Study of Finnish Retail Companies
Ryhänen, Anna (2026)
2026
Kauppatieteiden maisteriohjelma - Master's Programme in Business Studies
Johtamisen ja talouden tiedekunta - Faculty of Management and Business
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Hyväksymispäivämäärä
2026-03-16
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202603163239
https://urn.fi/URN:NBN:fi:tuni-202603163239
Tiivistelmä
Artificial intelligence is widely recognized as one of the most transformative technologies of our time. In recent years, its rapid development has significantly reshaped business operations, including those in the retail sector. Retail companies are well-positioned to benefit from AI due to their large volumes of customer data and digitalized service environments. As the retail industry shifts from product-centric to increasingly service-driven logic, understanding how AI supports strategic marketing becomes increasingly relevant. In Finland, the dominance of a few major retailers gives this transformation a context of its own.
This study explores how AI enables marketing capabilities in large Finnish retail companies. It seeks to answer two research questions: 1) How do large retail companies in Finland leverage AI in different marketing-related information operations? and 2) How does AI enable the development of marketing capabilities at different levels in these companies? The research focuses on describing and analysing AI usage through the lens of information operations (acquiring, integrating, analysing, and interpreting information) and links these uses to a hierarchical model of marketing capability development.
The research was conducted as a qualitative multi-case study, utilizing semi-structured interviews with C-level representatives from three major retail companies in Finland. All interviewees held strategic-level responsibilities in their organizations and had prior involvement in AI-related initiatives. The study followed an abductive logic, combining theoretical insights with inductive interpretations of the interview data. The theoretical framework was based on literature on marketing capabilities and artificial intelligence, with a particular emphasis on the model of hierarchical marketing capabilities by Madhavaram & Hunt (2008), which illustrates how different types of resources support capability development over time.
The findings indicate that AI is applied in relation to all four information operations in each of the studied companies, although the extent and strategic orientation of its use vary. The analysis provides illustrative examples of how AI may support these information operations and offers tentative insights into how such uses may be associated with different approaches to the development of marketing capabilities. Based on the analysis, three tentative adoption profiles were proposed: 1) the Operational Traditionalist, emphasizing efficiency and process optimization; 2) the Pragmatic Explorer, selectively implementing AI tools with a cautious and incremental approach; and 3) the Strategic Integrator, viewing AI as a potential driver of longer-term innovation and differentiation. These profiles should be interpreted as exploratory analytical constructs that illustrate possible differences in how companies approach the role of AI in marketing capabilities. The findings of this study should be interpreted as exploratory and context-specific, providing initial insights that may inform future empirical research.
This study explores how AI enables marketing capabilities in large Finnish retail companies. It seeks to answer two research questions: 1) How do large retail companies in Finland leverage AI in different marketing-related information operations? and 2) How does AI enable the development of marketing capabilities at different levels in these companies? The research focuses on describing and analysing AI usage through the lens of information operations (acquiring, integrating, analysing, and interpreting information) and links these uses to a hierarchical model of marketing capability development.
The research was conducted as a qualitative multi-case study, utilizing semi-structured interviews with C-level representatives from three major retail companies in Finland. All interviewees held strategic-level responsibilities in their organizations and had prior involvement in AI-related initiatives. The study followed an abductive logic, combining theoretical insights with inductive interpretations of the interview data. The theoretical framework was based on literature on marketing capabilities and artificial intelligence, with a particular emphasis on the model of hierarchical marketing capabilities by Madhavaram & Hunt (2008), which illustrates how different types of resources support capability development over time.
The findings indicate that AI is applied in relation to all four information operations in each of the studied companies, although the extent and strategic orientation of its use vary. The analysis provides illustrative examples of how AI may support these information operations and offers tentative insights into how such uses may be associated with different approaches to the development of marketing capabilities. Based on the analysis, three tentative adoption profiles were proposed: 1) the Operational Traditionalist, emphasizing efficiency and process optimization; 2) the Pragmatic Explorer, selectively implementing AI tools with a cautious and incremental approach; and 3) the Strategic Integrator, viewing AI as a potential driver of longer-term innovation and differentiation. These profiles should be interpreted as exploratory analytical constructs that illustrate possible differences in how companies approach the role of AI in marketing capabilities. The findings of this study should be interpreted as exploratory and context-specific, providing initial insights that may inform future empirical research.