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Formal and relational governance of artificial intelligence outsourcing

Author

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  • Erik Beulen

    (Tilburg University)

  • Albert Plugge

    (Nyenrode Business University)

  • Jos Hillegersberg

    (University of Twente)

Abstract

Outsourcing emerging technologies such as Artificial Intelligence (AI) are expected to impact organisations significantly, due to a tight labour market for AI expertise. However, how formal and relational governance effects Information Systems suppliers who provide AI services has not been studied. Based on an exploratory research amongst eight suppliers and two market research advisors, we conducted 18 expert interviews and found evidence how formal contractual and relational governance affects AI outsourcing. The results indicate various forms of contractual models in which some cater for clients’ needs specifically, e.g. outcome-based, experience-driven Service Level Agreements (SLAs). Our examination provides insights that formal and relational Information Systems (IS) outsourcing governance are complementary in cases where clients and suppliers co-develop AI. For our research, we adapted the outsourcing governance model of Lioliou et al. (Inf Syst J 24:503–535, 2014), including their emphasis on the psychological contract. We contribute to IS outsourcing literature by exploring, beyond contract management insights, differences between suppliers in providing AI services. Our study acknowledges that AI outsourcing shift the emphasis from a transactional type of arrangement to a relational type of outsourcing arrangement. In addition, the combination of both formal and relational governance mechanisms positively contributes to IS governance. Our study also confirms that the innovative character of AI positively contributes to the psychological contract in outsourcing AI.

Suggested Citation

  • Erik Beulen & Albert Plugge & Jos Hillegersberg, 2022. "Formal and relational governance of artificial intelligence outsourcing," Information Systems and e-Business Management, Springer, vol. 20(4), pages 719-748, December.
    • Handle: RePEc:spr:infsem:v:20:y:2022:i:4:d:10.1007_s10257-022-00562-7
    DOI: 10.1007/s10257-022-00562-7
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    References listed on IDEAS

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