AI Due Diligence in Dutch M&A Transactions

Practical AI diligence issues in Dutch software, SaaS and technology acquisitions

AI due diligence in Dutch M&A transactions refers to the process of assessing how a target company develops, uses, governs and depends on artificial intelligence systems, AI-generated outputs, data and AI-related infrastructure. In practice, AI diligence increasingly affects valuation, warranty negotiations, disclosure strategy, operational risk allocation and post-closing integration.

Artificial intelligence is rapidly becoming a transaction issue in Dutch M&A. Buyers are no longer only reviewing financial performance, contracts and intellectual property. They increasingly need to understand how a target company uses AI, whether the underlying technology and data are properly controlled, and how AI-related risks could affect compliance, scalability and investor protection.

This article forms part of the AI & Dutch Transactions Insights series, which focuses on practical AI-related issues in Dutch M&A, venture capital, private equity and Dutch BV governance.

AI diligence is becoming broader than ordinary IT diligence

Many buyers initially approach AI as part of ordinary technology diligence. In practice, AI-related risk often cuts across several workstreams simultaneously. Questions around intellectual property ownership may overlap with data protection concerns, commercial contracts, operational dependency and governance. As a result, AI diligence is increasingly becoming a coordination exercise between legal, technical and commercial advisors.

This becomes particularly relevant in cross-border transactions involving Dutch companies. Foreign buyers are often familiar with US-style technology diligence, but underestimate how AI-related rights, governance and liability issues interact with Dutch BV structures, shareholder arrangements and local compliance requirements.

Buyers increasingly focus on AI dependency

One of the main diligence questions is whether the target genuinely controls its AI capabilities. Many companies describe themselves as “AI-driven” while relying heavily on third-party providers such as OpenAI, Anthropic or cloud infrastructure platforms. Buyers therefore increasingly assess whether the company could continue operating if pricing, licensing terms or access rights change.

This issue matters commercially because dependency risk can directly affect scalability, margins and long-term enterprise value. In venture-backed and PE-backed transactions, investors also increasingly examine whether the target’s AI strategy creates sustainable competitive advantage or simply temporary market positioning.

AI-generated code and ownership issues

AI-assisted software development creates difficult ownership questions. Many Dutch software companies now use AI coding tools during development, but governance and documentation practices are often still immature. Buyers increasingly ask whether generated code is reviewed internally, whether open-source components are embedded in AI-generated outputs and whether developers uploaded confidential information into external tools.

These issues become particularly important where transaction value depends heavily on proprietary software or automation capabilities. In Dutch startups and scale-ups, key functionality is also frequently developed by freelancers or contractors, which may create additional uncertainty around IP ownership and assignment arrangements.

Training data and disclosure risk are becoming more important

Training data has become one of the most sensitive areas of AI diligence. Buyers increasingly examine whether the target had sufficient rights to use customer data, third-party data or publicly sourced information in AI-related activities. This is especially relevant in SaaS, healthcare, HR tech and data-driven businesses.

At the same time, AI-related issues increasingly affect disclosure strategy in Dutch M&A transactions. Sellers may need to disclose operational dependency on third-party AI providers, known model limitations, customer complaints, governance weaknesses or unresolved ownership questions. Generic disclosure language is often insufficient where AI capabilities materially influence valuation expectations.

AI governance increasingly affects investor perception

Investors increasingly assess whether companies have implemented workable AI governance rather than merely experimenting with AI tools. In practice, buyers want to understand whether the board receives AI-related reporting, whether acceptable-use policies exist and whether internal oversight mechanisms are in place.

Many companies currently use AI extensively without formal governance structures. That may not stop a transaction, but it can affect pricing discussions, indemnity negotiations and post-closing remediation requirements. Particularly in PE-backed and VC-backed companies, AI governance is increasingly becoming a portfolio oversight issue rather than only an operational matter.

AI warranties are evolving rapidly

Traditional warranty packages often do not fully address AI-related risks. Buyers increasingly seek protections relating to AI-related IP ownership, lawful use of data, compliance, operational reliability and governance procedures. Sellers, meanwhile, often resist broad AI warranties because legal standards remain uncertain and many businesses rely on third-party infrastructure providers.

As a result, AI warranty negotiations are increasingly becoming exercises in commercial risk allocation rather than purely technical legal drafting.

FAQ

What is AI due diligence in M&A transactions?

AI due diligence refers to the process of assessing how a target company develops, uses, governs and depends on artificial intelligence systems, AI-related data and AI-generated outputs. The purpose is to identify operational, legal, commercial and governance risks that could affect valuation, liability or post-closing integration.

Why is AI due diligence becoming more important in Dutch M&A?

AI increasingly affects software development, data processing, automation, customer services and operational decision-making. Buyers therefore need to understand whether AI-related risks exist around IP ownership, data rights, governance, compliance or third-party dependency.

Should buyers review training data rights during due diligence?

Yes. Buyers increasingly assess whether the target had sufficient rights to use customer data, third-party data or publicly available information in AI-related activities. Weaknesses in training data rights can create operational and legal risk.

Can AI-related risks affect valuation in Dutch transactions?

Absolutely. Dependency on external AI providers, weak governance, unclear ownership structures or insufficient disclosure can materially affect scalability, investor confidence and long-term enterprise value.

Practical AI diligence for Dutch transactions

AI-related transaction risk is developing rapidly. Buyers, investors and management teams increasingly need practical guidance on AI diligence, disclosure, governance and risk allocation in Dutch M&A, VC and PE transactions.

Dirk de Waard, partner at VentureLawyers, advises international investors, founders, management teams and companies on Dutch M&A, venture capital, private equity and governance matters involving Dutch BV structures and cross-border transactions.

For support with AI due diligence, AI-related transaction documentation or Dutch governance implementation, contact Dirk de Waard.