AI Representations and Warranties in Acquisition Agreements: The New Standard Clauses

AI Is Changing M&A Agreements Faster Than Most Lawyers Expected

Artificial Intelligence is no longer a niche technology discussed only by startups and technology companies.

Today, AI is integrated into products, internal operations, customer service systems, software platforms, healthcare tools, financial services applications, legal technology, cybersecurity solutions, and enterprise workflows.

As a result, AI has become an increasingly important topic during mergers and acquisitions (M&A).

Buyers evaluating technology companies are now asking a new set of questions:

• Who owns the AI models?

• What data was used to train them?

• Are there intellectual property risks?

• Are regulatory requirements being followed?

• Are third-party AI tools being used?

• Have customers been informed about AI usage?

• Are there cybersecurity concerns?

These questions are influencing acquisition agreements in ways that would have been uncommon only a few years ago.

Today, many lawyers involved in technology transactions are drafting AI-specific representations and warranties as part of their standard transaction playbook.

Source: https://www.cooley.com/news/insight/2025/2025-01-28-ai-ma-issues-for-buyers-and-sellers

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What Are Representations and Warranties?

Representations and warranties are statements made by a seller regarding the business being acquired.

These statements help buyers understand the condition of the target company before closing.

Common representations may address:

• Financial statements

• Tax compliance

• Intellectual property

• Contracts

• Employment matters

• Litigation

• Regulatory compliance

If a representation later proves inaccurate, the acquisition agreement may provide contractual remedies depending on the transaction structure.

As AI becomes a larger component of business operations, buyers are increasingly seeking additional representations focused specifically on AI systems and AI-related risks.

Source: https://www.americanbar.org/groups/business_law/

Why AI-Specific Representations Are Becoming Common

Traditional technology representations often focus on software ownership and intellectual property rights.

However, AI systems create additional considerations that may not fit neatly within traditional clauses.

For example:

• AI models may be trained using large datasets.

• Third-party AI tools may be integrated into products.

• Machine learning systems may evolve over time.

• AI outputs may create unique intellectual property questions.

• Emerging regulations may create new compliance obligations.

As a result, lawyers increasingly draft AI-specific provisions rather than relying solely on traditional technology representations.

Source: https://www.wsgr.com/en/insights

Why Buyers Are Paying Closer Attention to AI Risks

AI due diligence has become a growing focus in technology acquisitions.

Buyers increasingly review:

• AI governance policies

• Data usage practices

• AI development processes

• Model documentation

• Third-party AI licenses

• Regulatory compliance procedures

• Cybersecurity controls

The goal is not necessarily to eliminate risk.

Instead, buyers seek a clearer understanding of how AI is being developed, deployed, and managed within the target business.

Source: https://www.goodwinlaw.com/en/insights

Why Buyers Are Paying Closer Attention to AI Risks

AI due diligence has become a growing focus in technology acquisitions.

Buyers increasingly review:

• AI governance policies

• Data usage practices

• AI development processes

• Model documentation

• Third-party AI licenses

• Regulatory compliance procedures

• Cybersecurity controls

The goal is not necessarily to eliminate risk.

Instead, buyers seek a clearer understanding of how AI is being developed, deployed, and managed within the target business.

Source: https://www.goodwinlaw.com/en/insights

AI Ownership and Intellectual Property

One of the most important questions involves ownership.

Buyers frequently seek assurances regarding:

• Ownership of AI models

• Ownership of training materials

• Ownership of source code

• Ownership of proprietary datasets

Lawyers often focus on ensuring that the company has appropriate rights to the technology that supports its products and services.

Source: https://www.lw.com/en/insights

Data Rights and Data Usage

Data remains one of the most valuable assets in many AI businesses.

As a result, buyers frequently examine:

• Data collection practices

• Data licensing arrangements

• Data usage permissions

• Data retention policies

• Customer consents

Understanding how data was obtained and used can become an important part of transaction diligence.

Source: https://www.cooley.com/news/insight

Third-Party AI Tools

Many companies now rely on third-party AI platforms and services.

Examples may include:

• Large language models

• AI APIs

• Machine learning platforms

• Cloud-based AI services

Buyers increasingly seek visibility regarding:

• Vendor relationships

• License terms

• Usage restrictions

• Dependency risks

Lawyers often evaluate whether critical products rely heavily on external AI providers.

Regulatory Compliance

The global regulatory environment surrounding AI continues to evolve.

Many organizations now maintain internal governance programs addressing:

• Responsible AI

• Data privacy

• Transparency

• Risk management

• Security controls

Acquisition agreements increasingly address compliance-related issues where appropriate.

Source: https://artificialintelligenceact.eu/

Cybersecurity and AI Systems

AI systems frequently depend on large amounts of data and technical infrastructure.

As a result, cybersecurity remains an important diligence topic.

Buyers often review:

• Security controls

• Access management

• Data protection measures

• Incident response procedures

• Vulnerability management practices

Cybersecurity reviews are becoming increasingly integrated into AI transaction diligence.

Source: https://www.nist.gov/artificial-intelligence

How AI Due Diligence Is Changing M&A Transactions

A few years ago, AI reviews often formed a relatively small part of diligence.

Today, many technology transactions involve dedicated AI diligence workstreams.

These reviews may include:

• Technical assessments

• Data reviews

• Intellectual property reviews

• Vendor reviews

• Compliance reviews

• Security reviews

Law firms, private equity firms, investment banks, and corporate development teams are increasingly developing internal AI diligence frameworks.

Why Sellers Are Preparing Earlier

The growing focus on AI diligence is also influencing seller preparation.

Companies considering a future acquisition are increasingly documenting:

• AI governance procedures

• Data sources

• Model development processes

• Internal policies

• Vendor agreements

• Security controls

Early preparation can help streamline diligence discussions and reduce uncertainty during negotiations.

AI Governance Is Becoming a Major Topic

One of the most significant developments in recent years is the growing focus on AI governance.

Many organizations now maintain governance frameworks addressing:

• AI oversight

• Risk management

• Human review processes

• Documentation standards

• Vendor management

• Compliance monitoring

While governance approaches vary significantly between organizations, buyers often view mature governance practices as an important part of risk management.

Source: https://www.nist.gov/artificial-intelligence/ai-risk-management-framework

Why Lawyers Are Building AI Clause Playbooks

The pace of AI adoption has created a practical challenge for transactional lawyers.

Many acquisition agreements drafted several years ago did not contain dedicated AI provisions.

Today, lawyers are increasingly developing standardized approaches for addressing AI-related issues.

These internal playbooks may cover:

• AI representations

• AI warranties

• AI diligence requests

• AI disclosure schedules

• AI compliance reviews

• AI risk allocation provisions

Because the legal and regulatory landscape continues to evolve, many lawyers are updating these approaches regularly.

The Growing Role of Disclosure Schedules

As AI provisions become more common, disclosure schedules are becoming increasingly important.

These schedules may help identify:

• AI products

• AI vendors

• AI development tools

• Data sources

• Material contracts

• Regulatory inquiries

The goal is often to improve transparency regarding AI-related operations.

Questions Buyers Frequently Ask During AI Acquisitions

Many AI-related diligence requests now focus on practical questions such as:

• Does the company use AI in customer-facing products?

• Does the company rely on third-party models?

• What datasets support model training?

• Are AI systems documented?

• Are AI vendors properly licensed?

• Are governance policies in place?

• Are there known regulatory issues?

These questions continue to evolve as technology and regulatory frameworks develop.

What This Means for Modern M&A Practice

AI is becoming an increasingly important component of transaction planning, diligence, and contract drafting.

As a result, lawyers are spending more time evaluating:

• AI ownership

• AI governance

• AI compliance

• AI licensing

• AI intellectual property

• AI security

• AI risk allocation

• AI disclosure obligations

For many technology transactions, AI-specific representations and warranties are moving from optional provisions to commonly negotiated clauses.

The exact language will continue to evolve, but the broader trend appears clear:

AI has become a material transaction issue that buyers, sellers, and advisors increasingly address directly within acquisition agreements.

Key Takeaways

• AI-specific representations and warranties are becoming increasingly common in technology acquisitions.

• Buyers are conducting more detailed AI diligence reviews.

• AI ownership, data rights, licensing, and governance are key areas of focus.

• Lawyers are developing AI-specific drafting playbooks.

• AI disclosure schedules are receiving greater attention.

• Regulatory and compliance considerations continue to evolve.

• AI is becoming an important component of modern M&A risk allocation.

Disclaimer

This article is provided for general informational purposes only and does not constitute legal, tax, financial, regulatory, or professional advice. Readers should consult qualified advisors regarding specific transactions, agreements, or legal issues.

At Ovviously, we simplify complex legal and commercial topics for lawyers, founders, investors, in-house counsel, and business professionals.

Explore more insights on:

• AI Representations and Warranties

• AI M&A

• Artificial Intelligence Acquisitions

• AI Due Diligence

• Technology Transactions

• AI Governance

• AI Compliance

• AI Risk Management

• Intellectual Property

• Corporate Law

• Private Equity

• Acquisition Agreements

• Mergers and Acquisitions

• Transaction Structuring

• Legal Research

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