An emergent grounded theory of AI-driven digital transformation: Canadian SMEs’ perspectives

Amir Taherizadeh and Catherine Beaudry

Industry and Innovation, 2023, vol. 30, issue 9, 1244-1273

Abstract: Artificial intelligence (AI) empowers traditional firms to transform into Industry 4.0, enabling them to compete in an era of rapid technological advancements. However, AI adoption remains limited among Canadian firms. This research aims to identify the key dimensions of AI-driven digital transformation (AIDT) and develop a grounded theory that provides a rich and nuanced understanding of how the AIDT process unfolds within Canadian SMEs. The study reveals that the AIDT process is shaped by the interplay of five core dimensions: evaluating transformation context, auditing organisational readiness, piloting the AI integration, scaling the implementation, and leading the transformation. The first four dimensions follow a sequential, stage-like progression, while the fifth dimension is recurring and omnipresent, exerting a continuous impact on the other phases. AIDT is characterised as a path-dependent, slow evolutionary change spectrum that demands firms adapt by developing their sensing, seizing and reconfiguration capacities to evolve and sustain their evolutionary fitness. The study explores several theoretical and managerial implications that arise from the findings.

Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/13662716.2023.2242285 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:indinn:v:30:y:2023:i:9:p:1244-1273

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CIAI20

DOI: 10.1080/13662716.2023.2242285

Access Statistics for this article

Industry and Innovation is currently edited by Associate Professor Mark Lorenzen

More articles in Industry and Innovation from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().