Umeå University's logo

umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Navigating the organizational AI journey: The AI transformation framework
Umeå University, Faculty of Social Sciences, Department of Informatics.
Swedish Center for Digital Innovation, Department of Applied IT, University of Gothenburg, Sweden.
2026 (English)In: Business Horizons, ISSN 0007-6813, E-ISSN 1873-6068, Vol. 69, no 1, p. 89-100Article in journal (Refereed) Published
Abstract [en]

This article introduces the AI transformation framework, a structured approach organizations can use to navigate the complexities of AI integration. AI transformations are reshaping industries, but organizations often struggle to realize value from their initiatives. The framework presents three dimensions critical to successful AI transformation: automation, augmentation, and data richness. Automation involves delegating routine tasks to AI systems, augmentation enhances human decision-making through AI, and data richness ensures AI systems are effective and accurate. By visualizing these dimensions as a cube, the framework helps organizations strategically position their efforts to maximize AI's benefits. The AI transformation framework unfolds in three steps—path framing, path narrating, and path stretching—each addressing critical questions related to “what,” “when,” and “how” AI impacts the organization. Path framing helps executives define AI strategy, path narrating provides a temporal structure for implementation, and path stretching focuses on scaling AI efforts. The article offers practical recommendations for managing AI transformation, and by breaking down the AI transformation journey into manageable stages, organizations can better align their initiatives with their strategic goals.

Place, publisher, year, edition, pages
Elsevier, 2026. Vol. 69, no 1, p. 89-100
Keywords [en]
AI transformation, Artificial intelligence (AI), Automation, Data richness, Integrated intelligence, Path framing
National Category
Information Systems, Social aspects
Identifiers
URN: urn:nbn:se:umu:diva-244590DOI: 10.1016/j.bushor.2025.01.002Scopus ID: 2-s2.0-105016153716OAI: oai:DiVA.org:umu-244590DiVA, id: diva2:2002812
Available from: 2025-10-02 Created: 2025-10-02 Last updated: 2026-02-11Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Holmström, Jonny

Search in DiVA

By author/editor
Holmström, Jonny
By organisation
Department of Informatics
In the same journal
Business Horizons
Information Systems, Social aspects

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 305 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf