EconPapers    
Economics at your fingertips  
 

Service professions in Artificial Intelligence (AI)

Profession de service sous Intelligence Artificielle (IA)

Olfa Zramdini (), Mohamed Taieb Hamadi () and Sami El Omari
Additional contact information
Olfa Zramdini: UMA - Université de la Manouba [Tunisie]
Mohamed Taieb Hamadi: UNICAEN - Université de Caen Normandie - NU - Normandie Université
Sami El Omari: TBS Education - TBS Education [Toulouse Business School – École Supérieure de Commerce de Toulouse]

Post-Print from HAL

Abstract: Perceived as a revolutionary innovation, AI raises questions about its impact on services, particularly on professions. In this context, the collective understanding of AI by accounting professionals is of paramount importance for the future of their practice and judgement. We conducted a survey of 169 Tunisian accountants. Our results reveal a technical and largely positive understanding of AI, which is perceived as a transformative and efficient tool. However, this focus on productivity could obscure other aspects, particularly its human, ethical and social implications. This study therefore highlights the importance of careful consideration of the conditions for implementing AI in accounting practice, while questioning its potential benefits in terms of efficiency and modernisation of professional services.

Keywords: accounting profession; social representations; service; innovation; AI; représentations sociales; profession comptable; IA (search for similar items in EconPapers)
Date: 2026-06-24
References: Add references at CitEc
Citations:

Published in European Review of Service Economics and Management, 2026, 2026-1 (21), pp.147-178. ⟨10.48611/isbn.978-2-406-20692-7.p.0147⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:hal:journl:hal-05686075

DOI: 10.48611/isbn.978-2-406-20692-7.p.0147

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().

 
Page updated 2026-07-14
Handle: RePEc:hal:journl:hal-05686075