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Value creation and value capture for AI business model innovation: a three-phase process framework

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Åström, Josef, Reim, Wiebke, Parida, Vinit·2022·Review of Managerial Science
DOI 10.1007/s11846-022-00521-z
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Abstract

Abstract The rise of AI technologies is generating novel opportunities for companies to create additional value for their customers by applying a proactive approach, managing uncertainty, and thus improving cost efficiency and increasing revenue. However, AI technology capabilities are not enough—companies need to understand how the technology can be commercialized through appropriate AI business model innovation. When emerging technologies are introduced, business-model concepts often need to be significantly altered. This is necessary to fully capitalize on disruptive technologies because it is just as important to innovate the business model as it is to build advanced technology solutions. Therefore, the purpose of this study is to explain how AI providers align value-creation and value-capture dimensions in order to develop commercially viable AI business models. To fulfill our stated purpose, this study has adopted an inductive and exploratory single case-study approach centered on a market-leading provider of AI-related services. The findings are consolidated into a process framework that explicitly illustrates the key activities that companies need to perform concerning value creation and value capture for AI business model innovation and commercialization. The framework explains that AI providers need to follow three phases—namely, identifying prerequisites for AI value creation , matching value capture mechanisms, and developing AI business model offer . We also find that AI providers need to test and develop multiple AI business models and operate them simultaneously to ensure commercial success.

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  • AI adoption requires partnering agility to quickly coordinate and control actors' initiatives.

    “AI adoption requires partnering agility to quickly coordinate and control actors' initiatives.”

    From Artificial intelligence in innovation management: A review of innovation capabilities and a taxonomy of AI applications (2025) · cites this paper as Åström et al. (2022)

    The 'Developing AI capabilities' section says close collaboration between AI providers and customers is required, and §4.3 says actors should agree on their roles in the value-creation network. These passages support the need for coordination in AI offerings, but they do not establish a requirement for 'partnering agility' or for quickly controlling actors’ initiatives. Page numbers were not available in our copy. (LLM, conf=0.78)

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Citations

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Metadata

Authors
Åström, J., Reim, W., & Parida, V.
Affiliations
Luleå University of Technology (SE)
Corresponding author
Reim, Wiebke
ORCID
Venue
Review of Managerial Science
Publisher
Springer Science and Business Media LLC
Published
2022-01-20
Volume
16
Issue
7
Pages
2111-2133
ISSN
  • 1863-6683 (ISSN-L)
  • 1863-6691
DOI
10.1007/s11846-022-00521-z
OpenAlex
W4205498453
Cited by
195
References
5
Citations by year
2026: 37 · 2025: 57 · 2024: 50 · 2023: 43 · 2022: 8
FWCI
29.49
Type
journal article
Language
en
Open access
Licence
Locations
  • Review of Managerial Science (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
Lulea University of Technology
Topics
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Business Strategies and Innovation
  • Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Digital Innovation in Industries
  • Social Sciences › Business, Management and Accounting › Marketing › Service and Product Innovation
Keywords
value creation, value capture, commercialization of AI, business model development, process framework, disruptive technologies, AI services, business model testing

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