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Making AI a Reality: Intelligence Isn’t Fabricated

This is the first part of a two-part series discussing the real-world applications of artificial intelligence and the source of its information.

T he term artificial Intelligence (AI) is often thrown around loosely, whether referring to technological applications that drive consumption choices or instill fear into the hearts of lawyers who dread being replaced by soulless machines. In the latter sense, it is a term that conjures up incredible efficiency; technologies so powerful that they will inevitably replace humans entirely. AI certainly represents a major leap forward in helping legal departments become more effective. That need is only growing as legal resources get increasingly squeezed while demands increase.

Yet AI is often misunderstood. It is most effective when it is used to augment human input, not replace it. Moreover, AI can only work effectively when the data it is applied to work with is organized in a rational manner and processes are optimized. The contract management space is a good example of these points.  

For the purpose of this discussion, we define AI as technologies that can perform specific human tasks at least as efficiently as humans by leveraging algorithms that sift through and learn from volumes of data that enable more accurate determinations or predictions.1

[Related: Big Data, Internet of Things, and Artificial Intelligence: What Does It All Mean?]

The use of the term “artificial” in this context risks distorting the efficacy of AI, and the true role that human interface must play for it to be successful. Indeed, in that sense, there is nothing “artificial” about AI — it is a natural extension of human-constructed processes. Moreover, to be effective, AI requires significant human involvement and augmentation.

In the in-house corporate context, lawyers are struggling with the “more for less” challenge: Legal department workloads have increased (and continue to do so) due to a variety of factors, including globalization, regulatory expansion, and risk convergence. Yet, despite this surge in “demand,” law department budgets remain flat or are shrinking as a result of reduced global profit pools.2

Consequently, in-house lawyers are stretched thin and have more on their desks than they can handle in a workday.

This trend accentuates the inefficiencies that exist in the way many legal departments have organized themselves. In the contracting process, for instance, lawyers tend to review the same redlines time after time. Contract templates are inconsistent, and alternate provisions are often bespoke. What’s more, the wheel keeps getting reinvented in most legal departments, and longer contracting cycle times lead to higher transaction costs.

In response to these challenges, many in-house departments are re-examining and optimizing their work processes, starting by unbundling their service delivery models from top to bottom. They examine how work requests come in, where the work goes, and how it gets done. Work that previously was done by senior legal counsel, for example, might now be allocated to more junior colleagues or to automated self-service tools, depending on a pre-defined intake method designed to determine who or what is most efficient to execute the task.

The use of the term “artificial” in this context risks distorting the efficacy of AI, and the true role that human interface must play for it to be successful. Indeed, in that sense, there is nothing “artificial” about AI — it is a natural extension of human-constructed processes.


This development has driven a growing demand for AI-based technology in hopes that this technology will help create consistency, reduce costs, and speed up review cycles. Adding fuel to the fire are venture capitalists who invest in anything that purports to employ deep learning, machine learning, artificial intelligence, or natural-language processing. Indeed, judging by the number of solicitations for new products and invitations to AI-based conferences that we receive, there appears to be a perfect storm of irrational AI exuberance brewing in the legal profession.

Intelligence isn’t fabricated

The fundamental challenge with the term artificial intelligence in the world of contract management is that it is applied incorrectly. The solutions that AI offers in this context are not “artificial.” Rather, they harness the immense and aggregate amount of human intelligence that has been acquired and is manifested daily in the contract creation, negotiation, and review process.

But the problem isn’t the lack of human knowledge. It’s the fact that the human knowledge has not had, until recently, a mechanism to be efficiently leveraged — and that too in a non-bespoke, “democratic” manner. Many in the legal community, in fact, believe that contracting intelligence is not something that appears from the ether or originates from 1s and 0s. In other words, it is acquired, not fabricated.

[Related: The Next Frontier: A Legal Forecast for the Age of Artificial Intelligence]

The true value of AI in the legal context comes to fruition when the technology is applied as a means to enhance carefully considered improvements in the service delivery process. In other words, a process needs to be developed, rolled out, and overseen by humans before AI-based technology can truly facilitate that solution. Where it can go wrong is when AI itself is seen as a panacea for all ills, rather than being seen as a powerful tool that can augment a human knowledge-led solution.     

Augmentation trumps fabrication

If contract intelligence exists today, anything that increases or augments it is beneficial. As such, the term augmented intelligence better represents how such technology can be leveraged to enable humans to more efficiently apply their acquired knowledge. Most often, the true power and promise of AI in the legal context lies in augmenting acquired knowledge about how to improve processes, rather than in fabricating knowledge with a solution that is divorced from experience and reality.

Where it matters most: Obligation management

A common flaw in contract management is that most companies spend a lot of energy and time (often more than three months) negotiating a complex contract (with a three-year term), only to breathe a sigh of relief upon the closing of the deal. At that point, these companies store the executed documents in a static folder on a shared drive in their networks, clink champagne glasses, and forget all about it. Sound familiar?

Many in the legal community, in fact, believe that contracting intelligence is not something that appears from the ether or originates from 1s and 0s. In other words, it is acquired, not fabricated.


This approach makes it utterly impossible to effectively manage the obligations contained within the contracts that have just been negotiated. Nor will it allow the company to leverage the valuable insights it has just gained in the process that was closed for the next deal. Instead, obligations and deadlines already agreed run the risk of getting overlooked and the “deal wheel” gets reinvented the next time.

How can legal departments get out of this rut?

The solution is not to just roll out new technology. It is to understand, and then optimize the process used, leveraging the power of technology to enhance the result.

The most critical first step in improving any corporate contract management process is to create a high integrity repository of agreements, so that the company’s material obligations are centrally stored in an accessible manner. It is critical to do this at the outset of a contract management program, especially if a contract lifecycle management (CLM) software application is being deployed. A CLM application promises to automate the contract creation, negotiation, and approval processes of a company, so that lawyers can focus on more substantive issues, such as reducing cycle time, managing risks, and optimizing costs.

[Related: Realizing ROI from Contract Management Technology]

However, for this to happen, all (suspected) documents that make up existing obligations must be gathered and organized into rational categories. This enables relevant information to be extracted from the documents, with such information then getting attributed to specific “contract families.” This gathering and organizing of all relevant information allows corporate lawyers to better search, retrieve, and efficiently negotiate and manage the company’s obligations.

It is at this point in the process where the hype of AI often creates an unnecessary frenzy of excitement and fear.

Be sure to read the next installment of the “Making AI a Reality Series” that overviews AI’s current processes and predicts what to expect from AI in the future. 

SOURCES

1 Bjarne P. Tellmann, Building an Outstanding Legal Team – Battle-Tested Strategies from a General Counsel, pages 188-189 (2017 Globe Law and Business).
2 According to McKinsey, the global corporate-profit pool, currently valued at approximately 10 percent of global GDP, may shrink to less than eight percent by 2025, undoing in the next decade nearly all of the corporate gains made relative to the world economy over the past three decades. See McKinsey Global Institute, “The New Global Competition for Corporate Profits,” September 2015. © 2017 McKinsey & Co.

About the Authors

Prashant Dubey is president and CEO of Sumati, the leading global provider of augmented intelligence (AI) based Contract Migration services. Dubey is also the co-author of The Generalist Counsel: How Leading General Counsel Are Shaping Tomorrow’s Companies, published by Oxford University Press. He serves on the University of Chicago Alumni Board with Bjarne Tellmann.

Bjarne P. Tellmann is chief legal officer and general counsel of Pearson and a member of its executive team. Until very recently, he authored the ACC Docket “Career Path” column. His book, Building an Outstanding Legal Team: Battle-Tested Strategies from a General Counsel, was recently published by Globe Law and Business. He serves on the University of Chicago Alumni Board with Prashant Dubey, as well as on the University of Chicago Law School Council.


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