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Articles

N. 1 (2026)

Professional Training as a Mechanism of Cognitive Governance in Digital Transformation: A Comparative Multiple-Case Study of Italian Accounting Firms

  • Fabrizio Gritta
  • Xhimi Hysa
  • Rosario Bianco
  • Mario Calabrese
DOI
https://doi.org/10.3280/cgrds1-2026oa23329
Inviata
22 luglio 2026
Pubblicato
29-07-2026

Abstract

Digital transformation is profoundly reshaping professional service firms, affecting the nature of professional work, the role of technology, and the mechanisms through which value is created. Although the literature has extensively examined the effects of digitalisation on professional activities and organisational models, the role of professional training in the governance of these transformations remains relatively underexplored. This study addresses this gap by conceptualising training not merely as an individual investment in human capital, but as an organisational mechanism that influences professional judgement and the strategic adaptability of organisations. Drawing on a qualitative, theory-driven comparative multiple-case study of 30 Italian accounting firms undergoing digital transformation and based on semi-structured interviews, the study highlights the existence of a systematic trade-off between shortterm efficiency and medium- to long-term adaptability. The findings show that training pathways primarily focused on procedural knowledge foster rapid initial productivity but tend to reinforce technological dependence and limit the ability to address non-standard situations. By contrast, the integration of theoretical and conceptual content in training supports the development of professional judgement, mitigates automation bias, and contributes to the evolution of the service model. The study contributes to the literature on professional service firms and digital transformation by showing how training can be interpreted as a mechanism of cognitive governance and, more specifically, as a driver of different knowledge structures shaping technological adaptation trajectories in knowledge-intensive organisations.

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