On June 14, 2018

What Does AI Mean to the Future of Work?

By Sharan Gurunathan, Executive Vice President and Principal Solutions Architect

One of the most exciting areas in technology today is in the emerging field of artificial intelligence (AI). But there are a lot of misconceptions about what AI really is – and what it means to the future of work. The technology industry as a whole is still on the bleeding edge when it comes to artificial intelligence. With compute engines like IBM Watson that are primed for AI processes, we have the capability to create ingenious AI-based solutions that can empower human beings to be more productive by accelerating repetitive and tedious decision-making processes that can now be accomplished more effectively in the background. This doesn’t mean people will be replaced by machines.  It means their skills will be augmented and supported by machine learning capabilities that can free the human beings to do other more important work.  AI, therefore, is the future of work – and we can either embrace it now and find out how to make it work for us or we’ll be left behind.

Despite the “cool” factor AI brings to the table, practicality demands that we look for real-world applications that deliver a return on investment that makes both business and financial sense. As an early adopter of AI technology, we’ve worked closely with IBM for over a year now to create an AI-based Contract Review Automation solution that will help medium- to large enterprises reduce the complexity and manual labor involved in analyzing procurement contracts.

The solution will allow our clients to compare and contrast procurement contract language, discerning what should and should not be included in a contract, flagging only a handful of documents for human review. While the solution is best suited to procurement environments today (i.e., retail, government or real estate), we see a growing number of use cases on the horizon.  And this isn’t just theory – we have real-world clients already employing this technology – and enjoying its benefits immensely. In fact, after investing the time to properly train the system, we have seen customers improve their contract review times by as much as four times their previous output.  Where a paralegal is tasked with reviewing 30 contracts for an enterprise-size retailer, for example, and if it normally takes each paralegal one hour to review each contract, our solution can significantly speed the process, allowing five or six contracts to be reviewed in the same period of time. That can mean 150 to 180 contracts reviewed in the same time it once took those original 30 to be reviewed. By augmenting the reviewer’s intelligence, the solution accelerates the review process and improves productivity, freeing the paralegal or other legal authority from the tedious task of reading reams of legal documents and allowing them to perform larger volumes of work in shorter periods of time.

You’ll notice that I used the word “augment” there. While the buzz today is all about AI and the possibility of artificial intelligence one day eliminating human jobs, the term “augmented intelligence” may actually be a better descriptor of what today’s technology is designed to do. Augmented intelligence helps people do their jobs more effectively by delivering insights that accelerate human decision-making processes. Today’s AI-based contract review automation solutions are not a contract reviewer’s nemesis; on the contrary, they are more like a significant helping hand.

This kind of solution, however, is not right for every organization – even if they’re involved in procurement processes. To determine if an organization is well-suited for AI-based contract review automation, it’s critical to pay close attention to the amount of data being analyzed. Because the solution has to be “trained” to recognize patterns within data sets, there is a minimum threshold for success. Recognizing patterns in five pieces of data is difficult, while identifying patterns among thousands of data sets is relatively easy. Therefore, the larger the volume of work, the bigger the return on investment will be. Businesses analyzing 500 or more contracts per month are in the sweet spot for adoption, which typically means an AI-based contract review automation solution is best suited for medium to large enterprise organizations reviewing large numbers of contracts per month.

It’s also important to remember that, while your return on investment for a contract review automation solution may be big, it won’t be instant. Just like on-boarding a new employee, an AI-based contract analytics solution has a learning curve. It takes time to train the application to your company’s exact specifications. To reap the most rewards, you must be prepared to “teach” the system your own specific terminology – the nuances that the application is searching for inside the contracts it studies for your organization. Therefore, the time- and cost-savings don’t begin the very moment an automated contract review solution is adopted. Instead, the first 100 or more post-adoption contracts will still need to be manually scrutinized to allow the system to gather enough data to do its job thoroughly. The contract review process will then become automatic.

Want to Learn More? Explore the advantages of AI and machine learning, then discover what Coda’s AI-based Contract Review Automation solution can do for you. Read real-world client case studies that showcase other ways Coda is working with IBM Watson to create a Siri-like personal assistant for real estate and a virtual agent that interacts with customers. Finally, learn how digital transformation can become a disruptor’s tool for changing the playing field: http://ow.ly/meyn30khDnf.

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