A new frontier? Exploring artificial intelligence in corporate insolvency

Akintola, Kayode 2026. A new frontier? Exploring artificial intelligence in corporate insolvency. Laws 15 (4) , 79. 10.3390/laws15040079

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Abstract

Artificial Intelligence (AI) is a transformative phenomenon for global economies. Corporate insolvency regimes, equally, are economically significant as they promote preventive measures, company rescue/restructuring, liquidation of inefficient enterprises, and actions against errant directors. However, corporate insolvency is typically stymied by high costs and complexities associated with tasks such as asset management, investigations, and resolving creditor claims. These challenges are acute for stakeholders, such as Insolvency Practitioners (IPs), who often manage corporate insolvencies under information, time, and liquidity constraints. This paper presents and analyses findings from a survey (the survey was conducted by the research team of Akin Business Constructs and led by the author. All Figures/images used in this paper were generated by Akin Business Constructs.) on the use of AI in corporate insolvency proceedings. The objectives of the survey are to determine the existence, volume, and type of/rationale for AI use in corporate insolvency. This paper will, therefore, highlight the following: there is evidence of some usage of AI for varying tasks to support corporate insolvency proceedings; such usage points towards the adaptability of AI for simple and more complex corporate insolvency tasks; while the rationale for AI use in this context is predicated on efficiency gains, arguments against its use are principally centred on the accuracy of AI outputs; and the preponderance of AI use in this context is based on generic/non-specialised generative AI tools.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Cardiff Law & Politics
Publisher:	MDPI
ISSN:	2075-471X
Date of First Compliant Deposit:	6 August 2026
Date of Acceptance:	24 June 2026
Last Modified:	06 Aug 2026 13:00
URI:	https://orca.cardiff.ac.uk/id/eprint/188767

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