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

IF 3.4 3区管理学 Q1 ECONOMICS

Industry and Innovation Pub Date : 2023-08-27 DOI:10.1080/13662716.2023.2242285

Amir Taherizadeh, C. Beaudry

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引用次数: 1

Abstract

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.

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来源期刊

Industry and Innovation Multiple-

CiteScore

8.10

自引率

7.70%

发文量

期刊介绍： Industry and Innovation is an international refereed journal presenting high-quality original scholarship of the dynamics of industries and innovation. Interdisciplinary in nature, Industry and Innovation is informed by, and contributes in turn to, advancing the theoretical frontier within economics, organization theory, and economic geography. Theoretical issues encompass: •What are the institutional underpinnings for different organizational forms? •How are different industrial structures and institutions related to innovation patterns and economic performance?