Each day, the accomplishments of artificial intelligence multiply. AI recently solved Schrödinger’s equation in quantum chemistry. It regularly diagnoses medical conditions, pilots jets and fetches answers for our everyday queries. And now, it might dance better than you do.

The ever-improving abilities of AI are having marked positive impacts on a wide variety of industries and professions – especially corporate legal departments and the in-house counsel and legal operations professionals that run them. So, what can corporate legal professionals expect from AI in 2021?

Ari Kaplan, attorney, legal industry analyst, author, technologist and host of the Reinventing Professionals podcast, recently interviewed Nick Whitehouse, General Manager of the Onit AI Center of Excellence. Nick, who is the 2019 IDC DX Leader of the Year and Talent’s 2018 Most Disruptive Leader Award (as judged by Sir Richard Branson and Steve Wozniak), shared the AI trends that general counsel and legal operations professionals should keep an eye on for 2021, including:

  • Accelerated adoption – The pandemic has greatly affected the use of AI, spurring businesses and their corporate legal departments to recategorize it from curiosity to necessity. For example, 2020 saw many companies having to quickly reassess large numbers of contracts (such as leases). Legal AI allowed in-house teams to quickly assess their contracts and take action, helping their businesses survive and thrive.
  • Banishing the black box – Legal departments have historically been perceived as black boxes – work goes in and decisions come out slowly with little transparency. AI reduces the time spent on individual transactions, increasing transparency by enabling consistent use of playbooks and the ability for the business to self-serve.
  • Focus on solving in-house challenges  – The technology has shifted from a project-based law firm focus toward products that are centered on solving in-house problems like contract lifecycle management and AI contract review. With 71% of lawyers saying they are mired in manual tasks, these AI products can drive a massive amount of value for corporate legal.
  • AI in the near future – In addition to the shift from law firm focused AI services to more in-house based services, corporate legal can expect a greater blending of AI into contract lifecycle management and third-party review as well as AI-assisted document automation and billing management.

Visit the Reinventing Professionals website to listen to the podcast. You can also find it (and subscribe) on Apple podcasts.

/by

Contract review and drafting can take up to 70% of an in-house legal department’s time. The process is often painfully tedious and repetitive – especially if it is paper-based or spread across multiple systems like emails and private drives. Without a more effective digital enablement, the process to review and draft contracts is slow and inconsistent, requires enormous attention to detail and continues to be prone to costly errors. These challenges directly impact a company’s ability to reach favorable contract outcomes and achieve business objectives.

With ever-increasing pressure on legal teams to do more with less, enhancing contract efficiency through automation and the latest technologies represent a significant opportunity to improve business performance.

Artificial intelligence has the power to deliver significant productivity gains and allow lawyers to utilize their skills, experience and talent on higher-value business objectives. Onit undertook a study of its AI for the pre-signature contract phase, ReviewAI, to determine just how much it can help and found commendable results (you can read more about them here.)

Key takeaways from the study include:

  • Testers found that ReviewAI accelerated contract reviews and approvals by up to 70% and increased user productivity by more than 50%.
  • New users were immediately 34% more efficient with their time and 51.5% more productive. The average midsize company employs 28 lawyers who review 4,850 contracts annually. Unlocking more capacity – up to 51.5% – means those same lawyers can now process 2,498 more contracts annually. It’s like adding nine lawyers to your team.
  • The team leader, a senior lawyer, was able to reallocate 15% of his time from contract work and team management to higher-value activities.
  • The efficiency and productivity gains from using ReviewAI increased over time, allowing corporate legal departments to optimize team performance, reallocate resources to engage the business better and reduce the amount of contract work handled by external counsel.

To learn more about artificial intelligence and contract review and drafting, read about the study’s results.

/by

TAR Solutions for a New Decade

These days, it seems impossible to talk about eDiscovery or document review without mention of Technology Assisted Review (TAR). In its broadest use as a technical term, TAR can refer to virtually any manner of technical assistance – from password cracking to threading to duplicate and near-duplicate detection. In its narrower use, TAR refers to techniques that involve the use of technology to predict (or to replicate) the decision a human expert would make about the classification or category of a document. In this narrower sense, TAR often comes with a version number – TAR 1.0, TAR 2.0, and more recently, TAR 3.0. While some are inclined to advocate for the superiority of a single approach, each version has its merits and place, and understanding the underlying process and technology is crucial to selecting the right approach for a specific discovery need.

We recently authored a white paper to offer a discussion of the variables to consider when choosing the right TAR workflow for a specific matter, as well as the main principles behind different TAR solutions. By doing so, we make the claim that true preparedness lies in understanding the range of core technology within the TAR landscape, and further knowing how and where to access the right combination of people, process, and technology to meet any discovery need.  If you or your team have had mixed results with TAR, or want some guidance on deciding your approach with TAR in your next matter, you may find this paper helpful.

TAR Solutions for a New Decade

/by Brian Meegan

Expanding data volumes are having a significant impact on ediscovery, but what are the specific challenges being faced? Lighthouse’s Nick Schreiner outlines six challenges when working with large data sets and offers up insights into how to address these challenges with data re-use, AI, and big data analytics in a recent blog: https://lnkd.in/dYjcY6W

/by Nick Schreiner

eDiscovery itself is a big data challenge, but recent advances in AI and machine learning can help mitigate risks by breaking down the silos of individual cases and leveraging prior case data. Lighthouse’s Karl Sobylak discusses the benefits of bringing technology to bear to understand large data sets at scale in a recent blog: http://ow.ly/QbzZ50COKK8

/by Karl Sobylak

As data volumes continue to grow so does the need for AI and machine learning. In fact, adopting AI can be a catalyst for revitalizing your organization’s ediscovery model. Lighthouse’s Rob Hellewell makes the case for AI including cost reduction, lower risk, and improved win rates in a recent blog: http://ow.ly/MoNs50CMwws

/by Rob Hellewell

Artificial intelligence, advanced analytics, and machine learning are no longer new to the ediscovery field. While the legal industry admittedly trends towards caution in its embrace of new technology, the ever-growing surge of data is forcing most legal professionals to accept that basic machine learning and AI are becoming necessary ediscovery tools.

However, the constant evolution and improvement of legal tech bestow an excellent opportunity to the forward-thinking ediscovery legal professional who seeks to triumph over the growing inefficiencies and ballooning costs of older technology and workflow models. In this article, we provide you with arguments on how leveraging the most advanced AI and analytics solutions can give your organization or law firm a competitive and financial advantage, while also reducing risk.

/by Rob Hellewell

As the proponents of policy and creators of contracts, it’s well understood that the legal department’s job is, first and foremost, to manage risk. This involves identifying potential legal and regulatory issues as soon as possible, developing a profile of potential legal risks, avoiding those risks with compliance programs, and dealing with the ones that slip through the cracks.

What is perhaps less well understood is how dramatically the concept of “risk” has evolved in recent years. Between digital transformation and technological innovations, new data privacy laws, cyber vulnerabilities, and an increasing spotlight on corporate culture, values and diversity practices — risk management today is not your grandmother’s limitation of liability clause. For today’s legal departments, risk management goes hand-in-hand with data stewardship. What type of information is retained or destroyed is becoming just as important as how information is organized and leveraged. Yet, data disparity is on the rise.

/by Onna

When we set out with the goal of enabling knowledge workers across dispersed enterprise teams to gain control of their data, we didn’t start small. We knew that if we built a solution that worked for the most onerous, meticulous, and urgent use cases, like eDiscovery, we were on to something.

That’s why we’re thrilled to receive the LegalTech Breakthrough Award for eDiscovery Solution of the Year.

LegalTech Breakthrough selected our Knowledge Integration Platform for its representation of “a new category of legal tech products that doesn’t just “collect data,” but connects, centralizes, indexes, and processes it — transforming data into accessible, secure, and private knowledge.”

/by Onna

Forms, passports, driver’s license, scanned images: ProSearch Privacy Suite uses #deeplearning models built on the latest advancements in #NaturalLanguageProcessing and computer vision techniques to identify protected private information. #DataPrivacy

/by Brian Meegan