How AI can make contract negotiation more efficient and empower legal resources to do more important (and valuable) work
Let’s face it; the current methods for contract negotiations are — at best — inefficient. Typically, they’re performed in a silo through a series of email exchanges. Globally, this approach wastes billions of dollars. A recent IACCM survey reported that “when there is any form of an amendment to the approved standard, a staggering 85% of such agreements are subject to legal review”. The result is higher costs and delays. Some argue that the additional expense is justified by the need to reduce risk. Yet, the report also stated that “[o]nly a very small percentage — perhaps around 5% — have grasped the point that many of the risks they perceive are illusory, that their legal department is innately conservative and that real change depends on new thinking.” A new approach is required, one that “seeks to eliminate or minimize the question?” So, where should we look for that change?
One alternative is so-called “no-touch” contracts. We encounter these almost daily, usually in the form of terms of service that are signed or accepted without changes. They make the contracting process extremely efficient. Such no-touch arrangements can be suitable for purchases or sales of commodity goods and services. But, their one-size-fits-all model is a limiting factor preventing more widespread adoption.
Some organizations control costs by setting monetary thresholds in negotiations. They limit review for contracts below a specific value. As there isn’t always a direct correlation between risk exposure and agreement value, this strategy is inherently flawed. For example, a lower value contract may have more risk than higher value agreements if the agreement calls for the processing of personal data.
A better way to balance the need to customize certain transactions and manage costs and risks is through self-service contracts. A self-service agreement has built-in, automated review and negotiation capability. It risk-scores incoming redlines and responds appropriately to each amendment. It utilizes artificial intelligence to:
- accept a change,
- reject a revision and explain why, or
- modify the redline and replace the edit with a fallback term, or perhaps adjust another provision in the agreement to narrow the scope or impact of the change.
Additionally, to prevent individuals from gaming the system, rules can be set to cap the number of revisions and optionally risk rank the provisions.
A shift towards an automated review of redlines—at least, as an initial pass—is not only plausible, it’s likely. When considering the value of contracts strictly in terms of revenue, the majority of contracts requiring some revisions are subject to manual negotiation, while a handful of such agreements are of the no-touch variety. Self-service agreements—occupying the middle ground—may become the dominant mode of contracting. This will substantially reduce the need for manual review and traditional negotiation.
The value of this shift should not be underestimated. Given that billions of negotiated contracts are executed globally every year, eliminating even a small percentage of the email exchanges common to them (and the hourly fees that accompany their creation) translates into billions of dollars of annual savings. Couple the savings with the fact that self service-contracts necessarily free up legal resources to focus on more valuable, higher-level tasks; it becomes a question of when—and not if—a shift towards automation will become the norm.