The Use Of Generative AI In Corporate Governance And Deal Advisory

In today's fast-evolving corporate landscape, technological innovation is reshaping how deals are governed. Among the most transformative tools is Generative Artificial Intelligence (GenAI), which is rapidly moving beyond data analysis to play an active role in legal drafting support.

Generative AI: more than just due diligence

While GenAI has already made significant strides in automating due diligence processes, its applications now extend far beyond. Leading companies and legal teams are testing GenAI tools for drafting critical deal documents such as Non-Disclosure Agreements (NDAs), term sheets, and board papers. Furthermore, AI-driven platforms are emerging to flag potential risks, and even suggest compromise language during deal discussions.

These AI-powered capabilities promise to enhance speed, efficiency, and accuracy — key factors in complex deal environments where timing is often crucial.

Critical legal risks and challenges of GenAI use

Despite its potential, deploying Generative AI in legal workflows involves substantial risks that demand cautious management:

• Confidentiality and data security: Uploading sensitive corporate data into AI platforms, especially third-party cloud-based tools, poses serious risks of data leaks or misuse. For example, confidential terms of a merger could be inadvertently exposed if proper data segregation and encryption are not ensured.
• Accuracy and accountability: AI-generated documents may contain inaccuracies, ambiguous clauses, or outdated legal standards. For instance, an AI-generated NDA might omit critical jurisdictional provisions, exposing the parties to unexpected litigation risks.
• Ethical and regulatory compliance: The legal profession is subject to strict rules on confidentiality, unauthorized practice of law, and duty of care. Using AI without adequate oversight risks breaching these obligations. There are growing regulatory discussions worldwide about setting clear boundaries on AI's role in legal advice.
• Bias and fairness: AI models trained on historical data may inadvertently embed biases that affect contract fairness or negotiation dynamics. This could result in unequal deal terms or perpetuate systemic disadvantages.
• Overreliance and automation bias: Parties may place undue trust in AI outputs, neglecting critical human judgment. For example, accepting AI-generated negotiation suggestions without scrutiny could lead to unfavorable deal terms or missed risks.

A radical reflection on AI risks: when the black box becomes a legal black hole

Beyond the well-known risks, there is a deeper, less visible challenge that often escapes immediate attention: the opacity of AI decision-making can create a 'legal black hole' where accountability disappears. Generative AI systems operate as complex "black boxes," producing outputs through layers of algorithms that even their developers sometimes struggle to fully explain. This opacity raises a fundamental problem for legal governance: if a contract clause or negotiation tactic is suggested by an AI, but the rationale behind that suggestion cannot be transparently understood or audited, how can parties truly assess its fairness, legality, or risk?

This creates a paradox: while AI promises transparency and efficiency, it may simultaneously obscure critical decision-making pathways, making it difficult to:

• Trace responsibility in case of errors or disputes,
• Challenge potentially unfair or biased AI-generated terms,
• Ensure compliance with evolving legal and ethical standards.

In other words, AI's black box nature risks creating an accountability vacuum — a 'legal black hole' where traditional mechanisms of oversight, explanation, and redress become ineffective.

Addressing this requires not only stronger human oversight but also a rethinking of legal standards to demand algorithmic explainability and auditability as prerequisites for AI use in sensitive legal domains.

The indispensable role of expert legal counsel

In light of these radical shifts and hidden risks, the guidance of experienced M&A lawyers is more vital than ever. Here are tangible ways expert counsel safeguards value and steers innovation responsibly:

• Tailored AI integration: lawyers help calibrate AI tools to the transaction's unique legal and commercial context, ensuring compliance with local laws and client risk tolerance.
• Risk mitigation through scrutiny: human expertise remains essential to detect AI oversights, ambiguities, or unintended consequences, protecting clients from hidden liabilities.
• Strategic negotiation advocacy: counsel combines AI insights with deep negotiation experience to craft flexible yet robust deal structures.
• Privacy and compliance assurance: legal teams negotiate AI vendor terms and enforce data protection policies to secure sensitive information.
• Dispute prevention and resolution: by establishing clear AI usage protocols and audit trails, lawyers preempt conflicts and foster smoother post-deal integration.

Best Practices for Responsible AI Adoption in Deal-Making

• Always maintain human oversight over AI outputs, never relinquishing ultimate judgment.
• Establish clear internal policies on AI use, data governance, and client consent.
• Invest in continuous training to keep legal teams updated on evolving AI tools and regulations.
• Foster cross-disciplinary collaboration among legal, IT, and AI experts to align innovation with ethical standards.

Navigating this transformation requires not only vigilance over risks but visionary counsel ready to embrace the opportunities and challenges of an AI-augmented legal landscape.

Importantly, despite the great help from the AI's tools, the human intelligence remains essential for the positive conclusion of a deal.

No doubt that the dialectics, empathy, psychology are not just replaceable by AI and are key to build and conduct the right relationship in the negotiations between the opposing lawyers and hit together the ultimate target shared by seller and buyer... doing the deal. One can say that while AI supports efficiency, it is the lawyers' judgment and interpersonal engagement that ultimately drive successful negotiations.

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