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- Holmström, Jonny, et al.
(författare)
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AI management beyond the hype : exploring the co-constitution of AI and organizational context
- 2022
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Ingår i: AI & Society. - : Springer. - 0951-5666 .- 1435-5655. ; 37, s. 1575-1585
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Tidskriftsartikel (refereegranskat)abstract
- AI technologies hold great promise for addressing existing problems in organizational contexts, but the potential benefits must not obscure the potential perils associated with AI. In this article, we conceptually explore these promises and perils by examining AI use in organizational contexts. The exploration complements and extends extant literature on AI management by providing a typology describing four types of AI use, based on the idea of co-constitution of AI technologies and organizational context. Building on this typology, we propose three recommendations for informed use of AI in contemporary organizations. First, explicitly define the purpose of organizational AI use. Second, define the appropriate level of transparency and algorithmic management for organizational AI use. Third, be aware of AI's context-dependent nature.
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| 2. |
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| 3. |
- Holmström, Jonny
(författare)
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From AI to digital transformation : the AI readiness framework
- 2022
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Ingår i: Business Horizons. - : Elsevier. - 0007-6813 .- 1873-6068. ; 65:3, s. 329-339
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Tidskriftsartikel (refereegranskat)abstract
- Strategies and means for selecting and implementing digital technologies that realize firms' goals in digital transformation have been extensively investigated. The recent surge in artificial intelligence (AI) technologies has amplified the need for such investigation, as they are being increasingly used in diverse organizational practices, creating not only new opportunities for digital transformation but also new challenges for managers of digital transformation processes. In this article, I present a framework intended to assist efforts to address one of the first of these challenges: assessment of organizational AI readiness—that is, an organization's ability to deploy AI technologies to enable digital transformation, in four key dimensions: technologies, activities, boundaries, and goals. I show that this framework can facilitate analysis both of an organization's current sociotechnical AI status and of the prospects for the technology's fuller value-adding, sociotechnical deployment. The AI readiness framework invites fuller theorizing of the roles that AI can—and will—play in digital transformation.
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| 5. |
- Holmström, Jonny, et al.
(författare)
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Orchestrating digital innovation: The case of the Swedish Center for Digital Innovation
- 2021
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Ingår i: Communications of the Association for Information Systems. - : Association for Information Systems. - 1529-3181. ; 48, s. 248-264
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Tidskriftsartikel (refereegranskat)abstract
- There is increasing interest in how digital innovation is facilitated and enacted in networks of diverse actors, i.e. heterogenous networks. However, while there is considerable evidence that firms can build key capabilities through engagement with external partners, we find a dearth of studies on how digital innovation is orchestrated in situations where an academic unit plays a facilitating role in the heterogenous network. We address this question employing a dynamic capabilities approach, and focusing on experiences from a national academic initiative, the Swedish Center for Digital Innovation (SCDI). SCDI was formed in 2013 and has adopted an engaged scholarship approach and a combination of activities designed to increase digital capabilities among partner organizations. We argue that the acquisition of new knowledge through external and internal sources stimulates firms and public sector organizations engaged in digital innovation to integrate such new knowledge with existing knowledge. Specifically, we demonstrate how SCDI’s core activities create increased integrative capabilities for the involved stakeholders, as well as offer lessons-learned and recommendations for academic units that wish to orchestrate digital innovation.
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| 7. |
- Kostis, Angelos, 1990-, et al.
(författare)
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Data work as an organizing principle in developing AI
- 2024
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Ingår i: Research handbook on Artificial Intelligence and decision making in organizations. - : Edward Elgar Publishing. - 9781803926209 - 9781803926216 ; , s. 38-57
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Bokkapitel (refereegranskat)abstract
- While data are often depicted as raw, neutral, and mere inputs to algorithms, we build on an emerging stream of research on data work viewing data as ambivalent, performative, and embedded entities, interwoven with organizing. We argue that in the process of developing AI, where epistemic uncertainty prevails as a key organizing challenge, data work serves as an organizing principle providing the logic through which behaviors are adopted, interpretations are made, and the collective efforts of domain experts and AI experts are coordinated. Prior research suggests that active involvement of both AI and domain experts is required for developing AI. Yet, domain experts and AI experts have distinct knowledge and understandings of domain specificities, meanings of data, and AI’s possibilities and limitations. Consequently, in AI initiatives, a key organizing challenge is epistemic uncertainty, i.e., ignorance of pertinent knowledge that is knowable in principle. We build a conceptual model deciphering three key mechanisms through which data work serves as an organizing principle supporting organizations to cope with epistemic uncertainty: cultivating knowledge interlace, triggering data-based effectuation, and facilitating multi-faceted delegations. These three mechanisms emerge when domain experts and AI experts work with and on data to define and shape trajectories of an AI initiative and make decisions about AI. This chapter contributes to the nascent body of research on data work by expounding the performative role of data as a relational entity, by providing a processual view on data’s interweaving with organizing, and by deciphering data work as a collectively accomplishment.
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