The AI Catalyst: Helping Corporate Counsel Add Strategic Value

Corporate counsel can harness AI to make analyzing and drafting contracts easier.

By  
on

Last month, we discussed how law firms can harness artificial intelligence to extract actionable information from the contracts in the document management system (DMS), effectively monetizing the information by increasing the efficiency, quality, and profitability of the contract drafting process.

This month we’re going to explore how the same concept, with some minor differences, can positively impact the operations of, and indeed the strategic value provided by, the corporate legal department (CLD). For the law firm model, we focused on the analysis of contractual clauses and preparation of standard forms. While these activities are of interest to in-house counsel, much of their attention — so as to maximize value and to become true strategic partners in the business — deals with what we’ll call “entity” or term analysis.

As in the law firm model, the CLD has a large corpus of contracts that typically (we can only hope) reside in a central contract management system (CMS). The primary difference is that each of these contracts represents obligations, rights and risks of the company. One responsibility of the CLD is to work with business owners to ensure that they are 1) aware of their obligations and 2) actively managing the same. While this may seem straightforward, the reality is often anything but. The sheer volume of contracts — many of which are long lived — combined with the reality of ongoing turnover both in the business and in the CLD virtually guarantees that there is no single person who has a strong grasp of the company’s contractual universe.

To compound this challenge, the contracts themselves are, of course, largely unstructured text with limited discoverable data. Herein lies both the challenge and opportunity: what if one could sort through the set of contracts, reverse engineer the term sheet for each, and make that information actionable? At that point, corporate counsel could move to a much more proactive position — for instance being able to notify the appropriate business owner six months before a contract auto-renews and work with the business owner to address any open issues in the contract.

That, in a nutshell, is exactly the promise that AI and machine learning (ML) technologies provide us.

The corporate counsel on whom we focus here are primarily interested in, essentially, reengineering the term sheets of all of the contracts that the business is party to. When done successfully and accurately, the CLD will be in a strong position to understand the universe of agreements to which the company is party; all of the obligations of the company pursuant to those agreements; and the key dates and deadlines associated with those agreements.

Let’s take a quick look at how this can work by examining some actual contractual language. Looking at two clauses, we ask ourselves, given the right tools, what kinds of useful information can be extracted from these clauses to the benefit of the corporate attorney?

Sponsored

Preamble: This Mutual Confidentiality Agreement (this “Agreement”) between ABC Inc., for itself and on behalf of all of its subsidiaries, divisions and Affiliated Entities (including all such subsidiaries, divisions and Affiliated Entities, the “Company”), and XYZ Corp, for itself and on behalf of all of its subsidiaries, divisions and Affiliated Entities ((including all such subsidiaries, divisions and Affiliated Parties, the “Prospective Party” and together with the Company, the “Parties” and each a “Party”), is entered into as of 26 September 2017 (the “Effective Date”).

Term and Renewal. This Agreement will commence on the Effective Date and continue for a period of three (3) years (the “Initial Term”). Following the Initial Term, this Agreement will automatically renew for up to four additional one (1) year terms (each, a “Renewal Term”), unless either Party provides the other Party with written notice of its intent not to renew at least ninety (90) days prior to the expiration of the then current term. This Agreement shall expire no earlier than 26 September 2020 and no later than 26 September, 2024 (any such relevant date, an “Expiration Date”).

On immediate inspection, we can see seven contract “entities” located in the above two clauses that are of immediate practical use. Harnessed correctly, technology can quickly provide the corporate attorney with what he or she needs to know about each entity:

  1. The type of agreement (mutual confidentiality)
  2. The business — is it a party to the agreement? (the Company is a party)
  3. The identity of the counterparty (XYZ Corp.)
  4. The effective date (26 September, 2017)
  5. The expiration date (no earlier than three years — and no more than seven years — from the effective date)
  6. Is the agreement evergreen i.e., does it automatically renew? (yes)
  7. If the agreement does automatically renew, what kind of advance notice is required for termination? (90 days’ written notice prior to the expiration of the then-current term).

Sponsored

This information is clearly important when examining any one particular agreement and really not that difficult to extract manually for a trained attorney given the luxury of time and when looking at a single document. However, the reality is that the CLD isn’t dealing with a few agreements — the CLD probably has a corpus of a thousand or more agreements. Having access to this (and additional entity) information becomes all the more critical in this scenario in order to answer simple but highly relevant questions — e.g., which agreements require notice within the next quarter?

Manual extraction of data in this scenario becomes untenable quickly. However, just as in the identification of clauses, ML technology can largely automate the extraction of metadata for each contract. This data in turn can be appended to the contract record in the CMS and made discoverable.

Consider the implications of having this data available for every contract and making that data easily discoverable:

  • Shift from reactive to proactive — With the ability to analyze and detect data conditions (such as a notice period approaching), corporate counsel is able to reach out to business owners and proactively inform them of legal items that require their attention.
  • A global view allows for optimization — The global view of contracts and terms allows corporate counsel to optimize many aspects of vendor spend. Are terms consistent across vendors, across agreements with the same vendor? How do terms vary across business units? Are there historical agreements that need to be reworked?
  • A global view allows for timely support of business initiatives — Divesting a business unit, complying with a new regulatory requirement (e.g., GDPR), negotiating a licensing agreement with a strict non-compete, acquiring a company… all of these require corporate counsel to assess — often under significant time constraints — both legal and business risk that can be characterized from the terms present in the firm’s contracts.

As in-house counsel seek to — and are expected to — offer strategic, enterprise-level leadership and analysis above and beyond pure legal analysis, “breaking down the contract” in order to build a global portrait with the assistance of a good machine-learning enhanced CMS ought to be a priority for all organizations.

May Goren Photography

Dean Sonderegger is Vice President & General Manager, Legal Markets and Innovation at Wolters Kluwer Legal & Regulatory U.S., a leading provider of information, business intelligence, regulatory and legal workflow solutions. Dean has more than two decades of experience at the cutting edge of technology across industries. He can be reached at Dean.Sonderegger@wolterskluwer.com.

Topics

, , , , ,