Switzerland: How Artificial Intelligence Is Transforming M&A Due Diligence and Transaction Risk

Artificial intelligence is changing the way mergers and acquisitions (M&A) are conducted in Switzerland. AI-powered tools can review extensive virtual data rooms, identify contractual provisions and highlight potential risks in a fraction of the time traditionally required.

For buyers and sellers, these developments offer opportunities to accelerate transactions, reduce costs and improve the consistency of due diligence.

However, the growing use of AI also raises important questions about confidentiality, legal responsibility and the allocation of transaction risks.

A missed contractual obligation, incorrectly assessed liability or overlooked regulatory requirement can have consequences extending well beyond the due diligence process. Such findings may affect the purchase price, contractual warranties, indemnities and ultimately whether a transaction can be completed.

The challenge for businesses is therefore not simply whether to use AI, but how to combine technological efficiency with experienced legal and commercial judgement.

AI Is Changing the M&A Due Diligence Process

Due diligence is a fundamental part of any M&A transaction, allowing prospective buyers to examine a target company’s legal, financial, operational and commercial position before committing to an acquisition.

Traditionally, this process has involved extensive manual reviews of contracts, corporate records, employment arrangements, intellectual property rights, regulatory documentation and other material information.

AI-assisted tools can now support many of these activities by identifying relevant provisions, organising large document collections and highlighting inconsistencies or potential areas of concern.

This can significantly improve efficiency, particularly in complex transactions involving multiple jurisdictions or substantial volumes of documentation.

However, the value of due diligence depends on more than the speed at which information is processed.

A system may identify hundreds of contractual provisions without determining which genuinely threaten the transaction’s commercial objectives.

Conversely, an important risk may be overlooked because it arises from the interaction between several documents rather than from a single identifiable clause.

For this reason, effective AI-assisted due diligence requires a clear review methodology, appropriate legal supervision and an understanding of the proposed transaction.

Preparing for AI-Assisted Due Diligence

The successful use of AI begins before a buyer receives access to the target company’s data room.

For sellers, AI-assisted vendor due diligence can help identify documentation gaps, contractual inconsistencies and potential legal issues at an earlier stage.

Addressing these matters before the sale process begins may reduce delays, improve the quality of disclosures and strengthen the seller’s negotiating position.

Nevertheless, AI can only analyse information that has been made available to it.

Incomplete contracts, missing annexes, undocumented arrangements and inconsistent records can undermine the reliability of an automated review.

Sellers must therefore ensure that the virtual data room is properly organised and that relevant documents are complete, accurate and appropriately classified.

The use of AI should also be addressed expressly in the transaction’s confidentiality arrangements.

Non-disclosure agreements, virtual data room rules and applicable data protection legislation may restrict the use of external AI systems to process confidential information.

In Switzerland, particular attention should be given to the Federal Act on Data Protection (FADP), together with contractual confidentiality obligations and the protection of trade secrets.

Parties should establish whether AI tools may be used, what information can be processed and which technical and contractual safeguards are required.

These arrangements may include secure enterprise systems, restrictions on data retention, controls on access and assurances that confidential transaction information will not be used to train publicly available AI models.

Clear rules established at the outset can help avoid disputes and unnecessary delays later in the transaction.

Why AI Cannot Replace Legal and Commercial Judgement

AI systems are particularly effective at identifying standard contractual provisions and extracting information from large document collections.

However, the most significant transaction risks frequently depend on legal interpretation, commercial context and the structure of the proposed acquisition.

Change-of-control provisions provide a useful example.

An AI tool may identify clauses in customer agreements, financing documents or supplier contracts that refer to a change in ownership.

Whether those provisions are actually triggered by the proposed transaction is a separate question.

The answer may depend on whether the acquisition involves a direct or indirect change of control, the wording of the relevant agreement and any restructuring undertaken before completion.

Similarly, AI may identify a termination right in a commercial contract without recognising the importance of that particular customer to the target company’s revenue.

A clause affecting a minor supplier may have little practical significance, while a similar provision involving a strategically important customer could materially alter the value of the business.

Several additional limitations require attention:

• Incomplete information: AI cannot reliably assess agreements, side letters or commercial understandings that have not been disclosed.

• Unusual contractual provisions: Bespoke liability limitations, exclusivity arrangements and price adjustment mechanisms may require detailed legal interpretation.

• Swiss legal requirements: Certain provisions must be assessed against applicable Swiss law, including Article 100 of the Swiss Code of Obligations and relevant competition legislation.

• Regulatory approvals: Merger control, investment-related restrictions and sector-specific approvals may depend on the wider transaction structure rather than individual documents.

• Commercial significance: Identifying a contractual risk does not establish its financial impact or determine how it should influence negotiations.

These limitations make targeted follow-up questions, management interviews and coordination between legal, financial and commercial advisers essential.

Translating Due Diligence Findings into Transaction Protections

The ultimate purpose of due diligence is not simply to produce a report. It is to ensure that identified risks are appropriately addressed in the transaction.

In a share acquisition, this generally means translating material findings into the Share Purchase Agreement (SPA).

An overlooked change-of-control clause could allow a major customer to terminate its contract following completion.

An undiscovered financing provision might result in early repayment obligations.

A missing regulatory approval could delay completion or prevent the transaction from proceeding.

Each of these issues may require a different contractual or commercial response.

Depending on the circumstances, the parties may negotiate:

• Purchase price adjustments: Reflecting identified liabilities or reductions in the target company’s value.

• Specific indemnities: Allocating responsibility for clearly identified risks or potential losses.

• Escrow or retention arrangements: Withholding part of the purchase price to provide security against particular liabilities.

• Conditions precedent: Requiring specified consents, approvals or other actions before completion.

• Additional warranties: Providing contractual assurances about particular aspects of the target business.

AI can help identify the information underlying these negotiations.

However, determining the appropriate protection requires an assessment of the likelihood, financial significance and legal consequences of the relevant risk.

The greatest value therefore arises when technological analysis is integrated with experienced transaction advice.

How AI Is Affecting Fair Disclosure and Warranty Claims

One of the more significant developments concerns the relationship between AI-assisted due diligence and the disclosure of information by sellers.

In Swiss M&A transactions, sellers commonly seek to limit warranty liability by disclosing relevant facts to the buyer before signing.

Depending on the wording of the SPA, information disclosed through the virtual data room or a disclosure letter may qualify or exclude particular warranty claims.

The concept of fair disclosure is therefore central to negotiations over contractual risk allocation.

Traditionally, buyers may argue that a material issue was not fairly disclosed if it was buried within extensive documentation or presented without sufficient clarity.

The growing availability of AI-assisted document analysis may influence how these arguments develop.

Sellers may contend that sophisticated search and analytical tools make relevant information easier to identify, even within substantial data rooms.

Buyers, meanwhile, may argue that disclosure should remain sufficiently clear and specific, regardless of the technology available to review the documents.

Importantly, the legal consequences will depend on the SPA’s wording, the circumstances of disclosure and applicable law. The use of AI does not automatically establish that a buyer knew, or should have known, every fact contained in a data room.

Parties should therefore pay particular attention to the contractual definition of fair disclosure and the treatment of buyer knowledge.

This may include negotiating:

• The standard of disclosure required to qualify warranties.

• Whether the entire data room is deemed disclosed.

• Whether information must be sufficiently identifiable and understandable.

• The extent to which knowledge is attributed to the buyer or its advisers.

• Anti-sandbagging provisions restricting claims based on known issues.

• Pro-sandbagging provisions preserving contractual remedies despite the buyer’s knowledge.

These matters can materially affect the availability of warranty claims following completion.

Implications for Warranty and Indemnity Insurance

Warranty and indemnity (W&I) insurance is another area in which AI-assisted due diligence is becoming increasingly relevant.

W&I insurance can provide protection against certain losses arising from breaches of warranties in an M&A transaction, subject to the policy’s terms, exclusions and underwriting requirements.

Insurers assess the scope and quality of the due diligence undertaken before agreeing to provide coverage.

As AI becomes more widely used, insurers may seek greater clarity about the tools employed, the methodology followed and the extent of independent legal review.

An automated document review without appropriate professional supervision may raise concerns about the reliability of the findings and the identification of material risks.

By contrast, a well-documented approach combining AI analysis with experienced legal assessment can help demonstrate the thoroughness of the due diligence process.

Businesses should also recognise that AI software providers commonly limit their contractual responsibility for errors or omissions.

Reliance on a technological platform is therefore not equivalent to obtaining legal advice or a professionally prepared due diligence report.

Clear responsibility for reviewing, validating and interpreting AI-generated findings remains essential.

Practical Considerations for Buyers and Sellers

Businesses considering AI-assisted due diligence in Swiss M&A transactions should establish an appropriate framework before the review begins.

1. Agree on permitted AI use

Address the use of AI expressly in confidentiality agreements and virtual data room rules, including any restrictions on external platforms or document exports.

2. Protect confidential information

Ensure that AI systems meet applicable contractual, cybersecurity and data protection requirements.

3. Maintain complete and organised documentation

Review the quality of the data room and identify missing documents, incomplete agreements and inconsistencies before relying on automated analysis.

4. Establish a legally supervised review methodology

Define the scope of AI-assisted analysis and ensure that material findings are assessed by appropriately qualified advisers.

5. Prioritise commercially significant risks

Connect contractual findings with the target company’s financial performance, customer relationships, operational dependencies and transaction structure.

6. Translate findings into contractual protections

Consider whether identified risks require purchase price adjustments, specific indemnities, additional warranties or conditions precedent.

7. Negotiate disclosure and knowledge provisions carefully

Ensure that the SPA clearly addresses fair disclosure, attributed knowledge and the preservation or exclusion of warranty claims.

8. Document the due diligence process

Maintain appropriate records of the tools used, the findings generated, the legal review undertaken and the decisions reached.

This may assist with transaction negotiations, W&I insurance underwriting and the resolution of subsequent disputes.

Conclusion

Artificial intelligence is becoming an increasingly valuable tool in Swiss M&A transactions, offering opportunities to accelerate due diligence, improve document analysis and reduce administrative costs.

However, technological efficiency does not eliminate the need for careful legal interpretation, commercial understanding and effective negotiation.

The most significant transaction risks often arise not from the absence of information, but from failing to recognise its importance or translate it into appropriate contractual protection.

For buyers and sellers alike, the most effective approach is to combine AI-assisted analysis with experienced M&A advisers who can evaluate the findings in the context of the transaction.

By establishing clear confidentiality safeguards, maintaining robust review procedures and negotiating appropriate risk allocation provisions, businesses can benefit from AI-driven efficiencies without compromising the legal and commercial integrity of their transactions.

By Vischer, Switzerland, a Transatlantic Law International Affiliated Firm.

For further information or for any assistance please contact switzerland@transatlanticlaw.com

Disclaimer: Transatlantic Law International Limited is a UK registered limited liability company providing international business and legal solutions through its own resources and the expertise of over 105 affiliated independent law firms in over 95 countries worldwide. This article is for background information only and provided in the context of the applicable law when published and does not constitute legal advice and cannot be relied on as such for any matter. Legal advice may be provided subject to the retention of Transatlantic Law International Limited’s services and its governing terms and conditions of service. Transatlantic Law International Limited, based at 84 Brook Street, London W1K 5EH, United Kingdom, is registered with Companies House, Reg Nr. 361484, with its registered address at 83 Cambridge Street, London SW1V 4PS, United Kingdom.