Use of AI in Due Diligence: Legal Risks and Compliance Issues

Abstract

Artificial Intelligence (AI) has rapidly transformed the process of legal due diligence across sectors such as mergers and acquisitions, banking, insolvency, corporate governance, data protection, intellectual property, and compliance investigations. Law firms, corporate legal departments, and compliance teams increasingly rely upon AI-powered tools for document review, contract analysis, risk assessment, fraud detection, and predictive analytics. While these technologies improve efficiency, reduce costs, and enhance accuracy, they simultaneously create significant legal and ethical concerns involving data privacy, confidentiality, algorithmic bias, cybersecurity, accountability, professional negligence, and regulatory compliance.

This article critically examines the growing use of AI in due diligence processes within the Indian legal framework while comparatively analysing international developments. The article discusses the intersection between AI governance and existing laws such as the Information Technology Act, 2000¹, the Digital Personal Data Protection Act², 2023, the Companies Act, 2013³, the Insolvency and Bankruptcy Code, 2016⁴, and professional obligations under legal ethics. It further evaluates the risks associated with automated decision-making and highlights the need for responsible AI governance mechanisms in legal practice. The paper concludes that although AI can significantly improve due diligence procedures, unchecked reliance upon automated systems may expose organisations and legal professionals to serious compliance and liability concerns.

Introduction

The rapid integration of Artificial Intelligence into the legal and corporate sector has significantly transformed the traditional process of due diligence. In recent years, law firms, financial institutions, multinational corporations, and compliance professionals have increasingly adopted AI-powered technologies to analyse documents, identify legal risks, review contracts, and monitor regulatory compliance. What once required weeks of manual examination by teams of lawyers can now be completed within a considerably shorter period through automated systems capable of processing large volumes of information simultaneously.

Due diligence occupies an important position in corporate transactions such as mergers and acquisitions, insolvency proceedings, venture capital investments, banking transactions, and corporate restructuring. The primary purpose of this process is to identify existing liabilities, compliance gaps, financial risks, contractual obligations, and possible litigation concerns before the completion of a transaction. Traditionally, this work depended entirely upon human expertise and detailed manual review. However, technological advancement has gradually shifted this process towards automation and predictive analysis.

Artificial Intelligence has emerged as one of the most influential developments in this area. AI-driven software can identify unusual clauses in contracts, classify documents, detect inconsistencies, analyse financial disclosures, and even predict potential legal disputes. These developments have undoubtedly improved efficiency and reduced operational costs. At the same time, however, they have raised serious legal and ethical concerns relating to confidentiality, data privacy, cybersecurity, algorithmic bias, and professional accountability.

The growing dependence upon AI in legal due diligence therefore creates an important question regarding the extent to which technology can be relied upon in matters involving legal interpretation and professional judgment. While AI may improve efficiency, it cannot entirely replace the reasoning, contextual understanding, and ethical responsibility expected from legal professionals. The increasing use of AI in due diligence consequently requires a balanced approach that encourages innovation while ensuring legal compliance and accountability.

Beyond operational efficiency, the integration of Artificial Intelligence into due diligence raises deeper jurisprudential concerns regarding the transformation of legal accountability. Traditionally, due diligence has been rooted in professional judgment, fiduciary responsibility, and contextual legal reasoning. The increasing dependence upon AI-assisted systems may gradually shift this responsibility from human expertise toward algorithmic assessment, thereby complicating standards of negligence, liability, and professional care. From a governance perspective, this development creates important questions concerning whether automated legal assessments can satisfy the threshold of “reasonable diligence” expected under corporate and professional law. Consequently, AI should not merely be viewed as a technological innovation, but as a structural force capable of redefining legal risk allocation in commercial transactions.

Meaning and Scope of Due Diligence

Due diligence refers to the process of careful investigation conducted before entering into a legal or commercial transaction. It is intended to provide a comprehensive understanding of the legal, financial, operational, and regulatory position of a business entity.

In corporate practice, due diligence generally involves examination of statutory records, contractual obligations, litigation history, financial statements, intellectual property rights, labour compliance, tax liabilities, and regulatory approvals.

In India, due diligence has become particularly significant in mergers and acquisitions, foreign investments, insolvency proceedings, and large-scale commercial transactions. Companies and investors rely upon due diligence reports to evaluate the risks associated with a target entity before making strategic decisions.

Since such transactions often involve extensive documentation, the use of AI-assisted systems has become increasingly common. AI-based due diligence tools are capable of reviewing thousands of documents within a short duration. Through machine learning and natural language processing, these systems can identify missing clauses, compliance irregularities, unusual contractual terms, and possible legal risks. This technological shift has altered the manner in which legal professionals approach corporate investigations and compliance reviews.

In this context, the scope of due diligence is no longer confined to document verification alone but increasingly includes technological competence in evaluating the reliability, transparency, and legal compliance of AI-generated findings. Legal professionals must therefore exercise caution not only in interpreting corporate records but also in validating the systems through which such records are analysed. This dual responsibility introduces a modern compliance burden that merges traditional legal scrutiny with technological oversight.

Role of Artificial Intelligence in Due Diligence

Artificial Intelligence has substantially improved the efficiency of due diligence processes. One of the most important advantages of AI is the ability to rapidly process and organise large quantities of data. In traditional legal practice, document review was often repetitive, time-consuming, and expensive. AI technologies have simplified this process by automating document classification, extracting relevant information, and generating risk summaries.

In mergers and acquisitions, AI tools are frequently used to analyse contracts and identify clauses relating to indemnity, liability, dispute resolution, confidentiality, termination rights, and regulatory obligations. Similarly, in insolvency proceedings, automated systems assist in reviewing financial records, identifying fraudulent transactions, and assessing operational liabilities.

Another important feature of AI is predictive analysis. The legal implications of AI use in due diligence vary depending upon the nature of the technology deployed. Rule-based systems that automate basic document review generally present lower legal risks, whereas advanced machine learning models and predictive analytics systems create significantly greater concerns regarding transparency, explainability, and liability. For instance, contract analysis platforms such as Kira Systems⁵ may enhance transactional efficiency with relatively manageable risks, while predictive dispute analysis tools may influence legal strategy based upon opaque decision-making processes that remain difficult to audit. This distinction is important because the legal consequences of AI deployment are directly proportional to the complexity and autonomy of the system involved.

Certain advanced systems use historical data and compliance patterns to predict possible litigation risks or regulatory concerns. This enables corporations and legal advisors to make informed decisions before finalising transactions. AI also improves organisational efficiency by reducing the burden of repetitive tasks upon lawyers and compliance professionals.

Despite these advantages, AI cannot independently replace legal reasoning. Due diligence often involves interpretation of complex legal relationships, commercial realities, and regulatory frameworks that require human understanding and professional discretion. Consequently, AI should be viewed as a supportive tool rather than a substitute for legal expertise.

Legal Risks Associated with AI-Assisted Due Diligence

Although AI has introduced efficiency into legal practice, its use also creates several legal risks and compliance concerns.

One of the most serious issues relates to data privacy and confidentiality. AI systems involved in due diligence frequently process sensitive information including financial records, trade secrets, employee details, business strategies, and confidential communications. Since many AI tools operate through cloud-based platforms, the possibility of unauthorised access or data leakage cannot be ignored.

In the Indian context, the Digital Personal Data Protection Act, 2023⁷ becomes highly relevant because AI systems frequently process personal and commercially sensitive information. Organisations using AI technologies must therefore ensure lawful data processing, proper consent mechanisms, and adequate cybersecurity safeguards. Failure to comply with these obligations may result in financial penalties as well as reputational damage.

Another significant concern involves algorithmic bias. AI systems function on the basis of training data, and where such data contains inaccuracies or discriminatory patterns, the resulting outputs may also become unreliable. During due diligence, biased systems may incorrectly classify businesses, generate inaccurate compliance assessments, or produce misleading risk evaluations. Such errors may affect commercial decisions and create liability concerns for legal professionals and corporations.

The issue of transparency also presents an important challenge. Many AI systems operate through complex algorithms that are not easily understandable even to those using them. Lawyers may therefore rely upon conclusions generated by systems whose internal functioning remains unclear. This lack of explainability creates concerns regarding accountability and professional responsibility, particularly where AI-generated reports influence major commercial decisions.

Professional negligence is another area of concern. Advocates and legal professionals owe a duty of care towards their clients. If a lawyer relies excessively upon automated outputs without independent verification, errors in due diligence reports may expose clients to financial and legal risks.

The possibility of AI hallucinations represents one of the most serious practical risks associated with AI-assisted due diligence. Generative AI systems may occasionally produce false summaries, incorrect legal interpretations, or non-existent references while appearing highly convincing.

Cybersecurity threats further complicate the use of AI in legal services. Due diligence platforms are vulnerable to hacking, ransomware attacks, and manipulation of sensitive information.

Moreover, the absence of a clearly defined liability framework creates substantial regulatory uncertainty.

Regulatory Framework in India

India presently does not have a comprehensive legislation specifically governing Artificial Intelligence. However, several existing laws indirectly regulate the use of AI in legal and corporate due diligence:

• Information Technology Act, 2000⁸
• Digital Personal Data Protection Act, 2023⁹
• Companies Act, 2013¹⁰
• Insolvency and Bankruptcy Code, 2016
• Advocates Act, 1961¹¹

These laws address electronic records, cybersecurity, data protection, corporate governance, and professional ethics. However, they do not directly regulate AI-specific concerns such as algorithmic accountability and explainability.

Comparative International Regulation

Comparative legal developments provide valuable insight into the evolving governance of AI-assisted due diligence:

• European Union – Risk-based regulatory model
• United States – Sector-specific regulatory approach
• United Kingdom – Principles-based regulatory framework

India currently lacks a dedicated statutory framework governing AI in legal due diligence.

Judicial Developments

Although Indian courts have not yet extensively dealt with AI-specific due diligence disputes, several judgments concerning privacy and technology provide important guidance:

• Justice K.S. Puttaswamy v. Union of India¹²
• Shreya Singhal v. Union of India¹³
• Anvar P.V. v. P.K. Basheer
• Arjun Panditrao Khotkar v. Kailash Kushanrao Gorantyal¹⁴

These cases clarify privacy rights, digital freedoms, and evidentiary standards for electronic records.

Future Reform and Policy Recommendations

The sustainable integration of AI into due diligence requires a forward-looking regulatory framework that balances innovation with accountability. India should consider introducing sector-specific legal standards governing AI deployment in corporate, banking, and insolvency due diligence.

Such reforms may include:

• Mandatory algorithmic audits
• Explainability requirements
• Certification obligations for legal AI vendors
• Professional guidelines governing ethical AI use

Conclusion

Ultimately, Artificial Intelligence should be understood not as a substitute for legal expertise but as a transformative compliance instrument that reshapes the practice of due diligence. Its long-term legitimacy will depend upon the development of transparent governance structures, robust regulatory safeguards, and clearly defined professional accountability standards.

Without such safeguards, the efficiency benefits of AI may be outweighed by systemic legal vulnerabilities, thereby undermining both corporate trust and regulatory integrity.

Artificial Intelligence has undoubtedly transformed the process of legal due diligence by improving speed, efficiency, and analytical capability. However, the growing use of AI also creates substantial legal and ethical concerns. Excessive dependence upon automated systems may undermine transparency and accountability, particularly where important commercial decisions are based upon AI-generated outputs.

In the Indian legal framework, existing laws such as the Information Technology Act, the Digital Personal Data Protection Act, the Companies Act, and the Insolvency and Bankruptcy Code indirectly regulate certain aspects of AI-assisted due diligence. Nevertheless, the absence of a dedicated AI regulatory framework continues to create uncertainty regarding liability and governance standards.

The future of AI in legal due diligence must therefore be based upon responsible innovation and meaningful human oversight.

References / Bibliography

Books

1. Avtar Singh, Company Law, 18th edn. (Eastern Book Company, Lucknow, 2022).
2. Justice Yatindra Singh, Cyber Laws, 6th edn. (Universal Law Publishing Co., New Delhi, 2021).
3. Richard Susskind, Tomorrow’s Lawyers: An Introduction to Your Future (Oxford University Press, 2017).
4. Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 4th edn. (Pearson Education, 2021).
5. Pavan Duggal, Artificial Intelligence Law and Regulation in India (LexisNexis, 2023).

Statutes

1. The Information Technology Act, 2000.
2. The Digital Personal Data Protection Act, 2023.
3. The Companies Act, 2013.
4. The Insolvency and Bankruptcy Code, 2016.
5. The Advocates Act, 1961.
6. The Indian Evidence Act, 1872.

Case Laws

1. Justice K.S. Puttaswamy v. Union of India, (2017) 10 SCC 1.
2. Shreya Singhal v. Union of India, (2015) 5 SCC 1.
3. Anvar P.V. v. P.K. Basheer, (2014) 10 SCC 473.
4. Arjun Panditrao Khotkar v. Kailash Kushanrao Gorantyal, (2020) 7 SCC 1.
5. Faheema Shirin R.K. v. State of Kerala, AIR 2020 Ker 35.

Reports and Policy Documents

1. NITI Aayog – National Strategy for Artificial Intelligence
2. OECD Principles on Artificial Intelligence
3. European Parliament – Artificial Intelligence Act
4. Ministry of Electronics and Information Technology (MeitY)

Journal Articles and Online Sources

1. Surabhi Agarwal, “Artificial Intelligence and Corporate Compliance in India”, (2023) Indian Journal of Law and Technology.
2. Rishabh Sharma, “AI Governance and Legal Liability in India”, (2022) Journal of Indian Law and Society.
3. SCC Online Blog
4. LiveLaw
5. Bar and Bench
6. Jus Corpus
7. Indian Journal of Law and Legal Research (IJLLR)