Whether we like it or not, we are moving towards a more seamless automated era in both business and household life – with technology such as Amazon’s Echo “Alexa” already part of daily routines. As artificial intelligence (A.I.) continues to shape and accelerate the way we handle information and process data, this evolution is also leading to an increase in business efficiency.
According to a recent study by Accenture, A.I. has the potential to increase profitability by $ 14 trillion in gross value added (GVA) by 2035. In statistics published in the same report, the financial sector can only capitalize on AI technologies to “free workers from mundane, repetitive tasks like f. such as general customer inquiries and mortgage reviews “- benefiting from $ 1.2 trillion in additional GVA by 2035.
When it was initially invented, there was fear that artificial intelligence could take full control and dominate content production like the novelist machines in George Orwell’s 1984. However, this technology is proving to be a game-changing game with an upswing in the adoption of A.I. to demonstrate that any initial fear around has been effectively overcome.
Technological development is nothing new and nothing to fear – ever since the industrial revolution of the late 18th century, the world has seen factory jobs replaced by robotics, typewriters replaced by PCs and many more examples of technological advancements. It has often been assumed that human-held roles are somewhat secure, protected and irreplaceable for data, intellectual and language-driven tasks – such as contract creation and other legal documentation. This is still to some extent, but many barriers to logic are being overcome through smarter use of document automation.
Advanced Productivity Tools in A.I. the landscape of the legal world has led to increased optimism and positivity as technology now has the power to analyze documents and sift through them in the search for relevant information to perform basic human tasks. This A.I. technique is known as natural language processing and is used to scan, extract information and then accurately predict only information that is relevant only to certain legal cases or claims.
This positivity around data-rich business boosts A.I. backed by legal giant Baker McKenzie, who says: “Despite previous hype attacks, a number of commentators believe renewed interest in AI is justified. Continuous and rapid advances in computing power as well as dramatic declines in computing costs has led to an explosion in the amount and availability of data – all of which become fodder for optimizing AI algorithms. “
Confidence in A.I.-driven technology has continued to develop over the past decade, with a number of multinational banks and law firms embracing this technology. Some of the world’s more innovative companies in these sectors have already implemented automatic contract analysis and automated document production tools. Data can now be extracted routinely and documents are created quickly and in a flawless format – helping to achieve consistency and minimize risk.
Dana Remus, a professor at the University of North Carolina School of Law, and Frank Levy, a working economist at the Massachusetts Institute of Technology, studied the key automation options available to attorneys at large law firms. Their paper concluded that if all new legal technology were put in place immediately, it would be estimated that technology could free up lawyers’ hours by 13%.
Their research also suggested that basic document review has already been outsourced or automated at large law firms, with only 4% of lawyers’ time now commonly spent on this task.
There are a number of software companies that provide cutting-edge technology to enable machine learning integration and automated document production and analysis – these include: Kira, Cognitive +, eBrevia, Luminance and Leverton.
One of the world’s top ten law firms has recently launched an innovative example of using Kira and document automation together for an issue involving a client facing thousands of litigation-related claims. Kira automatically extracted information from an in-house developed case management system, pushing key information into the document automation software, which then generated the documents the client needed. The law firm’s innovation team found that the combination of technologies created a smooth and complete solution by harmonizing an approach from both A.I. and document automation.
Another successful example of utilizing similar automation technology includes Margin Matrix, a joint venture between Allen & Overy and Deloitte, which automatically prepares legal documents to help banks comply with new financial rules. The tool reportedly cuts the time it takes to manually handle 10,000 contracts (on average, as any major bank has) from over 15 years in lawyer hours to just 12 weeks.
This automation and machine learning approach has also been rolled out at JPMorgan Chase & Co. to analyze financial offers. The COIN Program for Contract Intelligence performs the repetitive task of interpreting commercial loan agreements that, until the project went online in June, consumed 360,000 hours of work each year by attorneys and loan officers. The software reviews documents in seconds, is less prone to errors and never asks for annual leave.
Commercial banks and law firms are under more pressure than ever to “churn out” contracts, loan agreements and complex documents, increasing the risk of incorrect information and data errors. By using A.I. and automatic production of contracts and agreements reduces the difficulty of creating legal documentation and the rate of production increases dramatically.
The world also requires constant delivery models that are cheaper, faster and better. Recent developments give us a lot to be positive about in the coming years to achieve this, and we must realize that complete automation will not happen overnight. Blending existing practices in document automation with A.I. continues to reap gains in efficiency. Coexistence is the best way forward, and A.I. is not here to steal your job, well at least not for some time to come …