Artificial Intelligence Harm and Accountability by Businesses: A Systematic Literature Review

Michael Dzigbordi Dzandu, Sylvester Tetey Asiedu, Buddhi Pathak, Sergio De Cesare

2025

Abstract

This study reviews the literature on artificial intelligence (AI) harms caused by businesses, their impact on stakeholders, and the available remedial mechanisms. Using the PRISMA method, relevant articles were sourced from the Scopus database and critically analysed. The data revealed that only 38 articles were published on the topic between 2012 and 2024, with 21 of these in 2024 alone. Key AI harms identified include economic and employment displacement, user harm, bias and discrimination, the digital divide, and environmental harm. While an explicit AI harm accountability framework was not found, related frameworks were derived from six cognate areas: data governance, decision-making, ethical AI, legal frameworks, responsible AI, and AI implementation. Five themes—AI transparency, accountability, decision-making, ethics, and risk—emerged as central to the literature. The study concludes that accountability for AI harms by businesses has been an afterthought relative to the rapid adoption of AI during the review period. Developing a robust AI accountability framework to guide businesses in mitigating AI harm is therefore imperative.

Paper Citation

in Harvard Style

Dzandu M., Asiedu S., Pathak B. and De Cesare S. (2025). Artificial Intelligence Harm and Accountability by Businesses: A Systematic Literature Review. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 1012-1019. DOI: 10.5220/0013486100003929

in Bibtex Style

@conference{iceis25,
author={Michael Dzandu and Sylvester Asiedu and Buddhi Pathak and Sergio De Cesare},
title={Artificial Intelligence Harm and Accountability by Businesses: A Systematic Literature Review},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={1012-1019},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013486100003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Artificial Intelligence Harm and Accountability by Businesses: A Systematic Literature Review
SN - 978-989-758-749-8
AU - Dzandu M.
AU - Asiedu S.
AU - Pathak B.
AU - De Cesare S.
PY - 2025
SP - 1012
EP - 1019
DO - 10.5220/0013486100003929
PB - SciTePress