How do I use AI without exposing confidential deal data?

Using artificial intelligence (AI) with confidential deal data requires a different approach than using AI for everyday productivity. M&A documents can contain financial information, contracts, intellectual property, personal data and strategic plans, making uncontrolled uploads to external AI applications a potential information security risk.

The safer approach is to bring AI to the information rather than repeatedly moving sensitive information into separate applications. Deal teams should evaluate where data is processed, whether existing permissions remain enforced and whether AI activity can be governed and audited. Understanding the limitations of general-purpose AI tools is an important first step when developing an AI strategy for transactions.

Keep deal documents inside the controlled environment

The movement of confidential information can create additional exposure points.

A common AI workflow involves downloading a document from one system, uploading it into another application and generating an analysis. While convenient, that process can create additional copies of sensitive files and separate the AI interaction from the security controls governing the original deal environment.

Organizations should instead look for architectures that allow AI to interact with information where it already resides. This can preserve the chain of control around confidential documents while still allowing professionals to use AI for summarization, information extraction, document analysis and Q&A.

For M&A teams, a secure deal management platform can provide the underlying governance required to combine document security with AI-powered workflows.

Extend existing permissions to AI

Connecting AI to deal data should not give users broader access than they already have.

If a professional cannot access a particular contract, financial document or folder in the deal room, an AI tool should not be able to retrieve that information on the user's behalf. Existing user roles and document permissions should determine what information AI can access and what it can return.

Organizations should also require auditability. AI interactions involving confidential deal information should be governed and logged so administrators can maintain visibility into how transaction data is being used.

These principles are central to secure AI connectivity for dealmaking, where permission-aware access can allow AI applications to interact with deal information without bypassing existing security controls.

Establish rules for approved AI use

Technology alone does not eliminate AI-related risk. Organizations also need clear policies defining which tools can interact with transaction information.

Deal teams should know which AI applications are approved, what types of information can be analyzed and when additional review is required. Administrators should consider whether customer data is retained or used to train external models and how AI-generated findings are validated.

Human oversight remains essential. AI can accelerate analysis, but material findings should be checked against original documents before they influence transaction decisions.

Bring AI to deal data with DealCentre AI

SS&C Intralinks DealCentre AI™ provides an approach designed to combine AI capabilities with controlled access to confidential transaction information.

DealCentre AI includes Link, Intralinks' proprietary AI engine, which can summarize documents, identify sensitive information, extract critical data and answer questions about applicable deal documents. Intralinks states that customer data is not used to train third-party AI models.

DealCentre Connect expands this model by allowing compatible external AI tools to work with DealCentre information through the DealCentre Connect Secure Gateway. Instead of requiring teams to download and re-upload confidential files, the architecture brings AI to the deal data while maintaining data room permissions, governance and auditability.

Using AI securely in M&A is therefore less about avoiding AI and more about controlling how it interacts with information. Keeping data governed, permissioned and auditable can allow organizations to benefit from AI without unnecessarily exposing the confidential information at the center of the transaction.