Distributors’ AI adoption capability and willingness assessment: The case of Distributor Aftermarket Business
Handolin, Juho (2025)
2025
Tuotantotalouden DI-ohjelma - Master's Programme in Industrial Engineering and Management
Johtamisen ja talouden tiedekunta - Faculty of Management and Business
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Hyväksymispäivämäärä
2025-06-30
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202506307462
https://urn.fi/URN:NBN:fi:tuni-202506307462
Tiivistelmä
Artificial Intelligence (AI) is a continuously maturing topic that has been examined in previous literature and limitedly utilized in companies’ business. Adopting AI into company’s business can be assessed by its capabilities and willingness. Thus, companies’ need to have required capabilities and resources from Information Technology (IT), human, organizational, and environ-mental perspectives. In addition to capabilities, companies must be willing to face changes and challenges related to AI adoption. On the other hand, companies that are utilizing AI in their business operations could achieve several benefits that influence their overall performance.
The study was a qualitative descriptive case study that was commissioned by the company which is operating in manufacturing industry. The goal of the study was to identify and deepen understanding of the case company’s distributors’ capabilities and willingness to adopt AI-technology into their business, as well as to expand the cooperation. The research process included 10 interviews for individual distributors. The purpose was to describe and evaluate what kind of capabilities do distributors have, how motivated they are in terms of adopting AI and sharing information, and which kinds of benefits can be achieved.
The results met with the goals of the study and the study achieved its objectives. The distributors were observed to have different levels of capabilities and willingness. The willingness dimension was found to be at better level than the capabilities dimension. In general, human capabilities were the weakest, and organizational capabilities were the strongest ones. In addition, there were lots of potential benefits identified, such as improved inventory availability, optimized and reduced inventory levels, and increased sales. These kinds of benefits were seen as incentives for AI adoption.
There were some limitations made for the study. Although the capabilities were also assessed from the environmental dimension, the study was limited to cover only the case company and its distributors, not the whole supply chain. The sample size of the study was relatively small as 10 distributors were included for the interview phase. Then, the study did not consider the technical implementations or solutions, but it focuses on identifying the development areas for the future work.
The findings offer broader knowledge and insights of the distributors’ current status for the case company. Thus, the knowledge of distributors’ capabilities and willingness status could be used for two purposes in the future. Firstly, to design an implementation plan for AI adoption in-to distributors’ business. Secondly, to focus on developing areas and find solutions to strength-en them. Additionally, the framework constructed in work and used in the interviews could be possibly utilized in the future when assessing the features of other business-to-business (B2B) companies.
The study was a qualitative descriptive case study that was commissioned by the company which is operating in manufacturing industry. The goal of the study was to identify and deepen understanding of the case company’s distributors’ capabilities and willingness to adopt AI-technology into their business, as well as to expand the cooperation. The research process included 10 interviews for individual distributors. The purpose was to describe and evaluate what kind of capabilities do distributors have, how motivated they are in terms of adopting AI and sharing information, and which kinds of benefits can be achieved.
The results met with the goals of the study and the study achieved its objectives. The distributors were observed to have different levels of capabilities and willingness. The willingness dimension was found to be at better level than the capabilities dimension. In general, human capabilities were the weakest, and organizational capabilities were the strongest ones. In addition, there were lots of potential benefits identified, such as improved inventory availability, optimized and reduced inventory levels, and increased sales. These kinds of benefits were seen as incentives for AI adoption.
There were some limitations made for the study. Although the capabilities were also assessed from the environmental dimension, the study was limited to cover only the case company and its distributors, not the whole supply chain. The sample size of the study was relatively small as 10 distributors were included for the interview phase. Then, the study did not consider the technical implementations or solutions, but it focuses on identifying the development areas for the future work.
The findings offer broader knowledge and insights of the distributors’ current status for the case company. Thus, the knowledge of distributors’ capabilities and willingness status could be used for two purposes in the future. Firstly, to design an implementation plan for AI adoption in-to distributors’ business. Secondly, to focus on developing areas and find solutions to strength-en them. Additionally, the framework constructed in work and used in the interviews could be possibly utilized in the future when assessing the features of other business-to-business (B2B) companies.