How Is Artificial Intelligence Changing Corporate Law?
Artificial intelligence (AI) and machine learning (ML) are changing corporate law by automating document review, accelerating due diligence, improving contract analysis, and enabling predictive legal analytics. For in-house legal departments and outside counsel, these tools reduce cost and increase speed—but they also raise new compliance, liability, and governance questions. This article explains how AI is being used in corporate legal practice, what legal risks it creates, and what businesses should do to prepare.
Recent Regulatory Developments in AI (2024-2026)
The regulatory landscape surrounding AI has evolved rapidly, with major developments at the international, federal, and state levels that directly impact corporate legal practice.
- European Union (EU AI Act): The European Union’s AI Act introduces a risk-based system governing AI use. Its phased implementation through 2026 has significant implications for businesses operating globally.
- United States Federal Activity: In the U.S., AI governance continues to develop through executive orders and agency enforcement. Federal agencies such as the FTC, EEOC, and SEC are increasingly scrutinizing AI use in areas like consumer protection, hiring practices, and financial disclosures.
- State-Level Legislation: States are playing a growing role in AI regulation. Colorado’s Artificial Intelligence Act (SB 24-205), effective June 30, 2026, imposes obligations on developers and deployers of high-risk AI systems, particularly around algorithmic discrimination and transparency.
- Emerging AI Liability Trends: Courts are beginning to address AI-related liability, especially in cases involving copyright, data usage, and automated decision-making. These developments are shaping how responsibility is assigned for AI-generated outputs.
What AI Tools Are Used in Corporate Law?
AI-powered tools are transforming how legal departments operate by automating time-intensive processes and improving accuracy.
Key Applications:
- Automated Contract Review: Quickly analyzes large volumes of contracts, flagging key clauses and potential risks to save time and improve accuracy
- Clause Extraction and Comparison: Compares clauses against templates or past agreements to ensure consistency and highlight deviations
- Contract Drafting Assistance: Suggests standard language and clauses based on context, speeding up drafting and reducing errors
- Regulatory Monitoring: Tracks regulatory changes and alerts legal teams to maintain ongoing compliance
- Fraud Detection: Analyzes transaction patterns to identify anomalies and prevent potential fraud
How Does AI Improve Legal Due Diligence?
Due diligence is crucial in corporate transactions, including mergers and acquisitions. Traditional methods often require more time and effort. AI and ML streamline this process by automating data extraction and analysis, making it more efficient and thorough.
Key Applications:
- Document Review and Analysis: AI tools quickly review extensive document collections, extracting relevant information and identifying potential issues. This accelerates the due diligence process, allowing lawyers to focus on more nuanced aspects of transactions.
- Risk Assessment: ML algorithms assess transaction risks by analyzing historical data and identifying patterns indicative of potential problems. This enhances decision-making and risk management, providing valuable insights that inform strategies and decisions.
- Compliance Checks: AI-powered tools automatically verify compliance with regulatory requirements, ensuring that all aspects of a transaction adhere to legal standards. This reduces the risk of non-compliance and associated penalties, providing assurance for corporate transactions.
What Are the Legal Risks of Using AI in Business?
While AI and ML offer significant benefits, there are also challenges and ethical considerations to address:
- Data Privacy and Security: Ensuring the privacy and security of data is paramount. Legal departments must adopt data protection measures to safeguard sensitive information.
- Algorithmic Bias: AI systems can inadvertently perpetuate biases in the training data, leading to biased outcomes. Legal professionals must ensure AI tools are trained on diverse and representative data sets.
- Transparency and Accountability: AI systems’ decision-making processes must be transparent and explainable. Legal departments need to understand how AI tools arrive at their conclusions and ensure accountability for the outcomes.
- Ethical Use of AI: The ethical use of AI involves maintaining client confidentiality, ensuring fairness, providing transparency, and augmenting human judgment rather than replacing it.
How Does the EU AI Act Affect Businesses?
The EU AI Act introduces significant compliance obligations for businesses that develop, deploy, or use AI systems—particularly those classified as “high-risk.”
Companies must first determine whether their AI systems fall within regulated categories, such as those used in employment decisions, financial services, or critical infrastructure. If so, they may be required to:
- Conduct formal risk assessments before deployment
- Maintain detailed technical documentation and records
- Ensure transparency, including informing users when AI is being used
- Implement human oversight mechanisms
- Continuously monitor system performance and report issues
The law also has extraterritorial reach, meaning companies outside the European Union may still be subject to its requirements if their AI systems impact individuals within the EU.
For many businesses, compliance will require cross-functional coordination between legal, technical, and compliance teams, as well as the development of internal governance processes to manage AI-related risk.
How Should Companies Build an AI Governance Framework?
As AI adoption grows, companies must move beyond ad hoc use and implement structured governance frameworks.
Key Components:
- AI Risk Assessments: Identify and evaluate risks associated with AI systems before deployment
- Internal Policies and Controls: Establish guidelines for ethical AI use, data handling, and system oversight
- Cross-Functional Oversight: Involve legal, compliance, and technical teams in AI decision-making
- Ongoing Monitoring: Continuously evaluate AI system performance and compliance with evolving regulations
- Training and Accountability: Ensure employees understand AI risks and assign clear responsibility for oversight
Conclusion
AI and ML are transforming corporate law by improving efficiency, accuracy, and cost-effectiveness across contract analysis, due diligence, and compliance. As these technologies evolve, businesses must also navigate emerging legal and ethical risks. If you or your business are looking for assistance with your corporate law needs, reach out to a member of our team of experienced corporate attorneys to discuss your next steps.
Contributions to this blog by Ashley Smith.
