1. Introduction
Artificial Intelligence (AI) is reshaping professions across the globe. Law is no exception. From document review to predictive analytics, AI tools are increasingly being deployed to enhance efficiency, reduce costs, and improve decision-making. Insolvency practice, which involves the administration of distressed companies, the protection of creditor rights, and the maximisation of asset recovery, stands to benefit significantly from these technological advancements.[1]
But here is the uncomfortable question: is Nigeria’s legal framework ready for this transformation? The Companies and Allied Matters Act (CAMA) 2020 provides the primary legislative foundation for insolvency practice in Nigeria. It establishes the roles and duties of insolvency practitioners, outlines procedures for administration, liquidation, and corporate rescue, and sets standards for professional conduct. Yet CAMA 2020 was drafted before the current wave of AI adoption. It does not contemplate AI-assisted decision-making, algorithmic analysis of financial data, or the use of machine learning in asset tracing and fraud detection.[2]
This gap between technological reality and legal regulation creates significant challenges. This article examines the legal challenges and prospects of integrating AI into insolvency practice in Nigeria. It argues that while AI offers considerable potential to improve insolvency administration, its adoption must be guided by clear legal frameworks, professional guidelines, and robust safeguards.
2. Conceptual and Legal Framework of AI and Insolvency Practice in Nigeria
2.1 Concept of Artificial Intelligence in Legal and Insolvency Practice
Artificial Intelligence refers to the simulation of human intelligence processes by computer systems. These processes include learning, reasoning, problem-solving, and decision-making. In the legal context, AI encompasses a range of applications including natural language processing for document review, predictive analytics for case outcomes, machine learning for pattern recognition, and robotic process automation for routine administrative tasks.[3]
For insolvency practitioners, AI offers several practical benefits. Firstly, AI can assist in the early detection of financial distress by analysing financial statements, cash flow patterns, and market indicators. Secondly, AI tools can trace assets more efficiently than manual methods, identifying hidden or misappropriated assets through sophisticated data analysis. Thirdly, AI can process vast quantities of financial records rapidly, reducing the time and cost of investigations. Finally, AI can support corporate rescue efforts by modelling different restructuring scenarios and predicting their likely outcomes. These capabilities are not futuristic speculation.[4] They are already being deployed in jurisdictions with more advanced legal frameworks. The question for Nigeria is whether its legal and institutional infrastructure can support responsible AI adoption.
2.2 Legal Framework for Insolvency Practice in Nigeria
The primary legislation governing insolvency practice in Nigeria is the Companies and Allied Matters Act (CAMA) 2020. CAMA 2020 introduced significant reforms to Nigeria’s insolvency regime, including the introduction of administration as a corporate rescue mechanism, the streamlining of liquidation procedures, and the establishment of clear standards for insolvency practitioners.[5]
Under CAMA 2020, insolvency practitioners are officers of the court with fiduciary duties to creditors, shareholders, and other stakeholders. Their responsibilities include investigating the affairs of distressed companies, realising assets, distributing proceeds to creditors, and, where appropriate, proposing rescue plans. They are expected to act with competence, integrity, and impartiality.[6]
The legal framework, however, is silent on the use of AI. It does not address whether insolvency practitioners may rely on AI-generated information, how AI-assisted decisions should be reviewed, or who bears responsibility when AI produces erroneous outcomes. This silence creates legal uncertainty and exposes practitioners to potential liability.[7]
3. Legal Challenges of Applying AI in Nigerian Insolvency Practice
3.1 Accountability and Liability for AI-Assisted Decisions
The most fundamental challenge is accountability. When an insolvency practitioner relies on an AI system that produces an erroneous recommendation, who bears responsibility? . Under existing law, the insolvency practitioner owes fiduciary duties to creditors and other stakeholders. If a practitioner delegates decision-making to an AI system and that system produces a flawed outcome, the practitioner cannot simply shift blame to the machine. The courts would likely hold the practitioner responsible for failing to exercise independent professional judgment. This is consistent with the principle that professionals cannot escape liability by delegating their duties to technology.[8]
But this approach creates a dilemma. If practitioners are held strictly liable for AI errors, they may be reluctant to adopt AI tools at all. If they are not held liable, creditors may suffer losses without recourse. Striking the right balance is essential. One possible solution is to require human oversight of all AI-assisted decisions, with practitioners retaining ultimate responsibility while AI serves only as an advisory tool.
3.2 Data Protection, Confidentiality and Cybersecurity
Insolvency practice involves the processing of sensitive financial and personal data. Insolvency practitioners routinely handle information about company finances, creditor identities, employee records, and commercial transactions. The use of AI tools raises significant data protection concerns. The Nigeria Data Protection Act 2023 establishes a comprehensive framework for data processing. It requires data controllers and processors to obtain lawful consent, ensure data accuracy, implement security measures, and notify data subjects of breaches. Insolvency practitioners using AI must comply with these requirements. But compliance is not straightforward. AI systems often require large datasets for training and operation, increasing the risk of data breaches. The involvement of third-party AI providers complicates accountability. Cross-border data transfers, which may occur when using foreign AI platforms, raise additional jurisdictional issues.[9]
3.3 Transparency, Bias and Reliability of AI
AI systems are often described as “black boxes.” Their decision-making processes can be opaque, even to their developers. This lack of transparency poses particular challenges in insolvency practice, where decisions must be explained and justified to courts, creditors, and other stakeholders. If an AI system recommends a particular course of action, the insolvency practitioner must be able to explain the basis for that recommendation. This is not merely a matter of professional courtesy; it is a legal requirement. Under Nigerian law, insolvency practitioners are accountable to the court and must justify their decisions. An opaque AI system makes this impossible.[10]
Bias is another concern. AI systems learn from historical data, which may reflect existing inequalities or prejudices. If an AI tool is trained on data that systematically disadvantages certain types of creditors or debtors, its recommendations will perpetuate those biases. This raises questions of fairness and procedural justice. Reliability is equally critical. AI systems can make errors, sometimes in ways that are difficult to anticipate. In insolvency practice, errors can have devastating consequences including incorrect asset valuations, flawed recovery strategies, or unjustified corporate rescue plans. Practitioners must be able to assess the reliability of AI tools and to identify situations where AI is not fit for purpose.
3.4 Evidential and Regulatory Challenges
The use of AI-generated information in legal proceedings raises evidential questions. Can AI-generated reports be admitted as evidence? What weight should courts give to such evidence? Under the Evidence Act 2011, electronic evidence is admissible provided it is relevant and reliable. But AI-generated evidence presents additional challenges: the complexity of algorithms, the opacity of decision-making, and the potential for errors. Regulatory gaps compound these difficulties. There is currently no specific regulation governing the use of AI in insolvency practice in Nigeria. Professional bodies, such as the Association of Insolvency Practitioners of Nigeria, have not issued detailed guidance on AI adoption. This regulatory vacuum leaves practitioners without clear standards to follow.[11]
4. Prospects and Regulatory Measures
4.1 Improving Insolvency Administration through AI
Despite these challenges, the prospects for AI in Nigerian insolvency practice are considerable. AI can improve insolvency administration in several ways.
Firstly, AI can enable early detection of financial distress. By analysing financial statements, payment patterns, and market data, AI systems can identify companies at risk of insolvency. Early detection allows for timely intervention, increasing the chances of corporate rescue and maximising creditor recovery.
Secondly, AI can assist in asset tracing and fraud detection. AI tools can analyse complex financial transactions, identify suspicious patterns, and trace hidden assets. This capability is particularly valuable in cases involving fraud, misappropriation, or complex corporate structures.[12]
Thirdly, AI can accelerate the analysis of financial records. Insolvency practitioners currently spend substantial time reviewing documents, identifying inconsistencies, and reconstructing financial histories. AI can perform these tasks more rapidly and accurately, reducing costs and improving outcomes. Also, AI can support corporate rescue by modelling different restructuring scenarios and predicting their outcomes. This allows practitioners to make more informed decisions and to present credible rescue plans to creditors and the court. Lastly, AI can enhance creditor recovery by identifying optimal strategies for debt collection, asset realisation, and distribution. This increases the likelihood that creditors receive fair compensation.[13]
4.2 Towards Responsible AI Integration in Nigerian Insolvency Practice
Realising these benefits requires a framework for responsible AI integration. Several measures are essential.
Firstly, professional bodies should develop clear guidelines for AI adoption in insolvency practice. These guidelines should address issues of accountability, transparency, data protection, and reliability. They should also establish standards for the testing, validation, and documentation of AI tools. Secondly, human oversight must be maintained. AI should assist, not replace, professional judgment. Practitioners should review AI-generated recommendations critically, exercising independent judgment and taking responsibility for final decisions. The court should similarly scrutinise AI-assisted decisions.[14]
Thirdly, data protection safeguards must be strengthened. Practitioners should implement robust security measures, obtain lawful consent for data processing, and ensure compliance with the Nigeria Data Protection Act 2023. They should also conduct data protection impact assessments when deploying AI tools. Lastly, existing insolvency regulations may require amendment or supplementation. CAMA 2020 could be updated to address the use of AI, clarifying the duties of practitioners, the admissibility of AI-generated evidence, and the standards for professional conduct. Alternatively, subsidiary regulations or professional guidelines could fill the gap.[15]
5. Conclusion
Artificial Intelligence offers significant potential to improve insolvency practice in Nigeria. It can enable early detection of financial distress, enhance asset tracing and fraud detection, accelerate analysis of financial records, support corporate rescue, and improve creditor recovery. These benefits are not speculative; they are already being realised in other jurisdictions. But the integration of AI into insolvency practice is not without challenges. Accountability and liability for AI-assisted decisions remain unresolved. Data protection and cybersecurity concerns are acute. Transparency, bias, and reliability pose significant risks. Evidential and regulatory gaps create uncertainty and inconsistency. The responsible path forward is clear. AI should assist, not replace, professional and judicial judgment. Practitioners must exercise independent oversight, critically reviewing AI-generated recommendations and taking ultimate responsibility for their decisions.
[1] Godwin Emmanuel Oyedokun, Kabiru Aderemi Adeyemo and Simeon Olaosebikan Oni, ‘Emerging Technologies and Insolvency Law in Nigeria: An Examination of Technology and Innovation under CAMA 2020’ (2025) 23(1) Journal of Private and Property Law – Rivers State University 101 https://rsuppljournal.com.ng/journal/index.php/jppl/article/download/8/8 accessed 10 September 2026
[2] Kayode Akintola, ‘A New Frontier? Exploring Artificial Intelligence in Corporate Insolvency’ (2026) 15(4) Laws 79 https://www.mdpi.com/2075-471X/15/4/79 accessed 10 September 2026
[3] Michael Maduawuchi Uzomah and Prudence Onajite Eruetemu, ‘Artificial Intelligence and Digital Economy and the Economic State of Nigerians’ (2024) 4(1) Journal of Emerging Technologies 26 https://www.journals.jozacpublishers.com/jet/article/download/690/375 accessed 10 September 2026
[4] Ibid
[5] Bolanle Adebola, Kayode Olude and Sanford Mba, ‘Comprehending and Resolving the Challenges of the Nigerian Insolvency Law in Practice: The Performance Improvement Approach’ (2025) 25(1) Journal of Corporate Law Studies 145 https://www.tandfonline.com/doi/full/10.1080/14735970.2025.2495408 accessed 10 September 2026
[6] Samuel Ejiro Uwhejevwe-Togbolo and others, Legal Framework Governing Bankruptcy and Liquidation in Nigeria (Southam Publishers 2026) https://southam.pub/book-catalog/2026/978-9915-9869-0-6/978-9915-9869-0-6.pdf#page=18 accessed 10 September 2026
[7] Ibid
[8] Matthew Izuchukwu Anushiem and Uchenna Maryjane Anushiem, ‘Artificial Intelligence and Digitalisation of Legal Practice in Nigeria’ (2025) 2(2) Nnamdi Azikiwe University Journal of Law and Clinical Legal Education https://www.journals.ezenwaohaetorc.org/index.php/NAU-JLCLE/article/download/3544/3675 accessed 10 September 2026
[9] Ionel Didea and Diana Maria Ilie, ‘Artificial Intelligence (AI)-“Ally” in the Success of Insolvency and Restructuring Practices’ (2024) Legal and Administrative Studies 92 https://www.upit.ro/_document/304683/jlas_1_2024.pdf#page=92 accessed 10 September 2026
[10] Ucha Caroline Agom, ‘Digital Transformation and Corporate Regulation in Nigeria: Legal Challenges of Fintech, Cryptocurrency, and Virtual Corporate Transactions’ (2025) 6(3) Law and Social Justice Review https://njournals.org/index.php/LASJURE/article/download/932/853 accessed 10 September 2026
[11] Moses Peace Richard, ‘Legal Perspective on the Use of Artificial Intelligence in Corporate Governance in Nigeria: Potentials and Challenges’ (2024) 34(48) Journal of Legal Studies “Vasile Goldiş” 97 https://reference-global.com/download/article/10.2478/jles-2024-0016.pdf accessed 10 September 2026
[12] Akshaya Kamalnath, ‘The Future of Corporate Insolvency Law: A Review of Technology and AI-Powered Changes’ (2024) 33(1) International Insolvency Review 40 https://onlinelibrary.wiley.com/doi/full/10.1002/iir.1512 accessed 10 September 2026
[13] Ibid
[14] Biranchi Narayan P Panda, ‘Integrating Artificial Intelligence (AI) into Corporate Insolvency Mechanism in India: A New Era of Resolution’ (2025) International Journal of Law and Management 1 https://www.emerald.com/ijlma/article/doi/10.1108/IJLMA-09-2025-0388/1328059 accessed 10 September 2026
[15] Ibid
