Is generative AI safe for M&A?

Generative artificial intelligence (AI) can be used safely in M&A, but only when security, data governance and human oversight are built into how the technology is deployed. The question is not simply whether an AI model is secure. Deal teams also need to understand where confidential information goes, who can access it, how AI-generated outputs are controlled and whether activity can be audited.

That distinction matters because M&A involves some of an organization's most sensitive information, including financial records, contracts, intellectual property, employee information and strategic plans. As generative AI becomes part of dealmaking, organizations need a framework for balancing productivity with information security. Understanding the limits of general-purpose AI tools is an important starting point.

Keep sensitive deal information under control

One of the biggest considerations when using generative AI for M&A is what happens to transaction data.

Uploading confidential documents into standalone AI applications can introduce another information-handling environment. Before using any generative AI tool, deal teams should understand where data is processed, how long it is retained, whether it can be used for model training and which parties can access it.

A safer architecture brings AI to the transaction data rather than repeatedly exporting transaction data to separate applications. This can help organizations maintain existing document permissions and governance policies while still benefiting from AI-powered analysis.

For teams evaluating these controls, understanding the requirements of a secure deal management platform can provide a useful framework for assessing AI alongside document and workflow security.

Require permissions, governance and traceability

AI should not create a shortcut around existing data room controls.

If a user is restricted from viewing a particular document, an AI assistant should not expose information contained in that document through a generated answer. Permissions governing the underlying information should also govern what AI can access and return.

Traceability is equally important. When AI summarizes a contract, extracts information or answers a diligence question, professionals should be able to return to the underlying source material and verify important findings.

Auditability adds another layer of governance. Organizations should understand which AI tools can access transaction information and maintain visibility into those interactions. These principles are central to the emerging model of secure AI connectivity for dealmaking.

Keep humans responsible for deal decisions

Generative AI can accelerate document review, summarization, information extraction and Q&A, but it should not become the final decision-maker.

AI-generated responses can miss context or misinterpret why particular information matters. Legal, financial and transaction professionals should validate material findings before they influence valuation, negotiation or investment decisions.

The objective should be augmentation: automate information-intensive work while keeping professional judgment at the center of the transaction.

Use generative AI within a secure deal environment

SS&C Intralinks DealCentre AI™ integrates AI directly into the M&A lifecycle, including preparation, marketing, diligence and deal management.

DealCentre AI is powered by Link, Intralinks' proprietary AI engine. Link can summarize documents, extract critical information, identify sensitive information and answer natural-language questions about applicable deal documents with traceability to source materials. Intralinks states that customer data used by Link remains within its secure environment.

DealCentre Connect extends this model to compatible external AI applications. Its Secure Gateway is designed to bring AI tools to deal information without requiring teams to export sensitive documents, while maintaining data room permissions, governance and auditability.

Generative AI can therefore be safe for M&A when it operates within the right architecture. Security, permissions, traceability and human oversight should be treated as core requirements, not features added after AI has already been deployed.