How can AI identify risks in contracts?

Artificial intelligence (AI) can help identify risks in contracts by analyzing large volumes of legal documents, locating relevant provisions and surfacing information that may require closer examination. Instead of relying exclusively on manual review or keyword searches, deal teams can use AI to investigate contracts using natural-language questions and rapidly narrow their attention to potentially material issues.

During M&A due diligence, that capability can be particularly valuable. Contracts may contain change-of-control provisions, termination rights, renewal terms, financial obligations and other clauses that could influence transaction value or post-close operations. AI can accelerate the process of finding these provisions, allowing legal and deal professionals to spend more time evaluating their significance. This is part of the broader shift toward AI-powered due diligence.

Use AI to surface potentially important provisions

Traditional contract review often begins with search terms and manual reading. That approach remains important, but it can become difficult to scale when a data room contains hundreds or thousands of agreements.

AI can analyze document content and help professionals locate specific provisions or information across contracts. Rather than searching individually for terms such as "change of control," "termination" or "exclusivity," users can ask questions based on what they actually need to understand.

For example, a buyer might want to identify agreements that could be affected by an acquisition or understand contractual obligations associated with important customer relationships. AI-powered discovery can help surface relevant information for further investigation. Intralinks explores this transition from keyword search to contextual AI-powered M&A discovery.

Look for patterns across multiple contracts

Some risks become clearer when contracts are evaluated collectively rather than individually.

AI can help deal teams compare information across document sets and identify recurring provisions, obligations or inconsistencies. This can make it easier to determine where additional legal, financial or commercial review may be necessary.

Summarization and structured data extraction can also reduce repetitive work. Important information from multiple agreements can be surfaced in a more consistent format, making comparisons easier and helping professionals determine which documents deserve priority.

However, AI should not be treated as an autonomous legal reviewer. A potentially unusual clause is not necessarily a material risk, and its importance depends on the transaction. Intralinks' perspective on the AI-powered acquirer examines how buyers can use AI to surface insights while keeping professional judgment at the center of diligence.

Make traceability part of AI contract analysis

Identifying a potential issue is only useful if professionals can verify it.

AI used for contract diligence should provide a clear path back to the underlying documents. Legal teams need to confirm the language, context and applicability of important findings before they influence negotiations, valuation or transaction structure.

Security is equally important. Contract information is often among the most sensitive material in a transaction, so organizations should consider whether AI respects existing permissions and how confidential information is processed.

Analyze contract information with DealCentre AI

SS&C Intralinks DealCentre AI™ integrates AI-powered document intelligence directly into M&A workflows.

Link, Intralinks' proprietary AI assistant, can summarize complex documents and locate and extract specific information from files within the virtual data room. Ask Link allows users to ask natural-language questions across applicable deal documents and receive answers with references to source material.

These capabilities can help professionals investigate contractual issues without manually searching every agreement. The objective is not for AI to decide whether a contract represents an acceptable risk. It is to help deal teams identify relevant information sooner, investigate potential issues more efficiently and give legal and transaction professionals more time to determine what those findings mean for the deal.