Year: 2021

How Legal AI and Automation Work for Law Department Operations

Posted on February 19, 2021 by - Business Process Management, Company News and Events

Implementing legal AI and automation is not a one-size-fits-all proposition. With numerous forms of both technologies, it helps to examine specific use cases and the corresponding benefits that come to the table.

In the first part of this blog and podcast series, we outlined what AI is at its foundation. In part two, we tackled how artificial intelligence and law departments are already working together.

Now, we’re back for the third and final segment of his AI series, which covers the combination of legal AI and automation. With the many different types of legal automation and AI assistance available today, we have some crucial points to consider for automation and AI’s role in it.

Starting the Journey of Combining Artificial Intelligence and Law Departments

Start by asking yourself some basic questions about the drivers you’re trying to achieve through automation. Is your goal to increase productivity, efficiency and quality? Are you most concerned about risk mitigation and compliance? Or are you trying to be efficient about identifying trends and actionable insights with the data you currently have?

For example, if your goal is to enhance efficiency, contract AI software and automation can speed up contract approval by up to 70% and increase user productivity by 51.5%.

Your reason for automating your law department will have an impact on how you go about implementing it. Regardless of your goals, you always need to be considering how automation can help your legal department become more valuable to the rest of the organization.

The Different Types of Legal AI and Automation

Automation isn’t one-size-fits-all and there many varieties of it available now. Before you start implementing automation and legal AI, it’s helpful to understand the different automation types that exist today. The goals you have might impact the kind of automation you choose.

There are three significant types of automation, plus a fourth that ties them all together:

  1. Intelligent process automation (IPA) focuses on optimizing tasks that traditionally require some form of human interaction. It assumes that companies have already digitized business processes and created workflows. IPA uses software to perform processes and automate tasks while completing workflows and automating and integrating digital processes. It extends the scope of process automation that has capabilities for reading documents. Think OCR, machine learning and natural language processing. It also manages processes through event triggers and intelligent workflow and helps collate and process data across multiple systems. For example, in the legal domain, an IPA-based platform can read and analyze contracts to automate the identification, extraction and evaluation of contract terms, identify business-critical information such as contract entities and assess them against standard clause statements.
  2. Business process automation (BPA) is the technology-enabled automation of tasks that accomplishes a specific workflow or function. BPA has somewhat similar goals as IPA, but its primary goal is to automate a business process while improving and simplifying business flows. A critical difference between BPA and IPA is that IPA is more about optimizing existing digital workflows, while BPA is about digitization. An example of this in the legal world would be digitizing all incoming matter-related documents and forms, with BPA capturing and validating information in any format as soon as such information is available.
  3. Robotic process automation (RPA) uses intelligent automation technology to handle high-volume, repeatable tasks, enabling business users to devote more time to other, higher-value work. The distinguishing characteristic of RPA is its capacity for awareness and ability to adapt to changes in circumstances.
  4. Hyperautomation brings together several components of legal automation and AI and machine learning to amplify work automation. The goal of hyperautomation is to optimize and deliver work more effectively, more efficiently and at a lower risk to drive innovation. A crucial component of hyperautomation is the ability to include humans in the digitization process. Hyperautomation can provide insights into ROI and leverage AI to enable end-to-end intelligent automation. For example, consider a law firm utilizing two technologies – one that intelligently reads data and documents and the other being an RPA tool (robot). An incoming email from a client triggers the RPA robot to read the email and its attachment. It logs in to the client’s system as an accredited user and downloads the data to be processed by the reading tool. The tool reads all the document’s data (which a human usually had to do) and extracts the relevant information utilizing machine learning to pass back to the RPA robot to populate the case management system and the finance system. It then notifies the supervising partner of the critical case information. With hyperautomation, the time to open a file decreases from 90 minutes to 10 minutes. It meets the service-legal agreement for the first response and the file opening administration team – through AI-assisted automation – focuses on higher-value work for the more complex cases.

Once you understand the different types of legal AI and automation and what you’re trying to achieve through automation, you can start to develop and implement your ideal technology plan for your law department.

To hear more about legal AI and automation, the benefits of combining artificial intelligence and law departments and the essential elements to consider before deciding on technologies, you can listen to our entire podcast (see below.)

February Digest: The Latest in Legal Operations Trends and News

Posted on February 17, 2021 by - Artificial Intelligence, Business Process Management, Contract Lifecycle Management

Welcome to our February run-down of the latest in legal operations trends and news. In this digest, we dig into the results from the Association of Corporate Counsel’s 2021 Chief Legal Officers survey and how ADM controls legal spend. Experts will share real-life numbers that illustrate contract AI benefits and a new approach to legal operations maturity models. Finally, we’ll talk about CLOC and its strategy for expanding membership.

#1

Contract Management Tops General Counsel Wish Lists, According to Survey

 According to the 2021 Chief Legal Officers survey conducted by the Association of Corporate Counsel, corporate legal departments are pursuing more hiring as privacy and compliance challenges increase. More than 30% plan to add in-house lawyers and nearly half said they will send more work to outside counsel this year and increase headcount for corporate legal.

Artificial Lawyer analyzed the results as well, focusing on the types of legal technology GCs and CLOs want in the next two years. Taking first place: Contract management, with 67%. With contract AI accelerating contract approvals by up to 70%, it isn’t hard to understand why this is a priority corporate legal top brass.

The ACC survey includes feedback from 947 participants in 44 countries.

(sources: Corporate Counsel and Artificial Lawyer)

#2

ADM Legal Chief Redesigned Law Firm Relationships and Cut Spend. Here’s How.

In legal operations news regarding outside counsel spend, Cam Findlay, Senior Vice President, General Counsel & Secretary at Archer Daniels Midland, shares how his team significantly reduced legal spend. The company dropped its legal spend from 85% to 50% of its budget. How? The department relied on technology, best practices and a law firm panel.

As he explains to Bloomberg Law:

“One of the first things we did was get better technology. We put in place a matter management system that allows us to track every penny—well, we think we track every penny—of spending by an outside law firm. We can even track the diversity of the lawyers who are working for us, how many hours were done by women or people of color.

“We use Onit, and we were one of the first major companies to use it, I believe. It’s a very good system because it’s beyond just matter management and e-billing, and we use it for all sorts of purposes throughout the company. It’s a good platform that you can plug and play other aspects onto.”

He also discusses how the law firm panel – called the ADM Law Firm Alliance – helped drive them to their global spending goals:

“We sit down with our top firms early in the year, every year, and through our Onit system, we’re able to prepare a firm report card for them that shows how their rates compare to other law firms, how their staffing compares, in terms of whether they are partner heavy or associate heavy. It also shows how they’re doing in terms of the diversity of the team that they’re putting on our matters. That’s been a really effective tool. We can sit down with a firm and say, ‘Your team was 100% white male. Your competitors here have been able to put much more diverse teams on our matters. That’s something we want you to work on for next year.’”

(source: Bloomberg Law)

#3

How Effective is Contract AI for Legal? Here Are the Numbers.

A panel of experts from Adobe and Onit gathered at Legalweek(year) tackled the latest legal operations trends by discussing contract AI and its impact on corporate legal. Instead of general benefits, though, these presenters provided quantitative numbers showing how effective this technology is.

A recent study of contract AI found that:

  • New AI users become 34% more efficient with their time and 51.5% more productive
  • Contracts are reviewed and redlined in less than two minutes
  • The technology helps corporate legal reduce contract processing costs by 33%
  • Users can shift work to higher-value activities, with one senior lawyer reallocating 15% of his time from contract work and team management to more strategic endeavors.

To hear the panel discussion, visit here.

(source: Legalweek[year])

#4

A New Approach to Legal Operations Maturity Models

According to the 2020 State of the Industry survey by the Corporate Legal Operations Consortium (CLOC), there has been a steady growth trajectory in legal operations across organizations of all sizes. The outcome has been an increase in new hires and technology to deliver legal services efficiently, cost-effectively and across departments.

Nathan Wenzel, the co-founder of SimpleLegal, proposes an alternative to existing legal operations maturity models – one honed from working with more than 200 corporate legal departments.  While he outlines five distinct levels of legal operations maturity, he also emphasizes that the goal is to find the place in the spectrum that works best for your organization.

(source: Law Technology Today)

#5

CLOC Welcomes New Legal Technology Members

In 2016, CLOC allowed only in-house counsel as members. In 2019, they welcomed legal operations professionals. In the latest legal operations news, they’re opening the doors wider by inviting more members, including technology companies, service providers and law schools.

What should all CLOC members expect? According to Betsi Roach, CLOC’s executive director, there will be an expanded array of topics and perspectives. As she explains in the CLOC press release on the matter:

“Our members and the greater legal community are hungry for more resources to answer questions and advance their careers. Creating a place that champions diversity of ideas and thoughts will not only disrupt the business of law but will define professional growth paths and pave the way for future generations. This is an exciting advancement on our continued journey to make a real impact on both the legal industry and for those in our community to grow their networks.” 

To learn more about CLOC memberships, visit here.

(sources: Corporate Counsel and CLOC)

Discover More Legal Operations Trends with Lean Into Legal Ops

Speaking of legal operations, Onit is expanding our Lean Into Legal Ops virtual learning program to include even more members of the legal community and provide even more diverse content. Past webinars have included:

Get the inside track on legal operations trends, the very best events and helpful content from the legal community by joining Legal Into Legal Ops today. Visit this page to join.

Onit Honored as One of the Top Workplaces in Houston; Hear Why on this Podcast.

Posted on February 11, 2021 by - Company News and Events

With more than 14,000 employers, including 21 Fortune 500 companies, the competition to be named one of the top workplaces in Houston is stiff. That’s all the more reason why Onit is honored to be included as one of the Houston Chronicle’s Top Workplaces for the third year in a row, coming in at number 30 for 2020.

We also earned the program’s only Communications Award. The award, also based on employee feedback, is reserved for the organization continually going above and beyond to keep employees informed.

The Houston Chronicle’s Top Workplaces awards program recognizes the most sought-out businesses in the Houston region, based on the feedback of more than 37,000 employees gathered through a third-party survey. The award considers 15 factors critical to any company’s success, including culture, organizational health, engagement, satisfaction, leadership, cooperation, communication, work-life balance, training, pay and benefits.

The Inside Scoop on Onit

What exactly makes Onit one of the best places to work in Houston? In a recent podcast (see below), employees Angela Mulligan, director of organizational health, and Carlos De Leon, senior recruiter, joined Nash Gates to share why they think Onit won this award – and what it means to prospective employees, including:

  • Entrepreneurial culture – Onit encourages employees to have an entrepreneurial spirit while focusing on innovation and creative problem-solving. Have an issue you want to discuss? There’s an open-door policy from the top down.
  • Fast-paced growth – Onit completed three acquisitions in less than two years and recently expanded its offerings with an AI platform and contract AI software. Activities like this, coupled with our emphasis on its customers and innovation, earned us an impressive triple-digit percentage increase in 2020 revenue growth, number seven among the fastest-growing companies in Texas according to Inc. and number nine on the Houston Business Journal’s Fast 100 list.
  • Customers – Onit works with some of the largest companies in the world, with more than 45 Fortune 500 customers.
  • Dedication to employees – While other companies focused on workforce reductions during the onset of the pandemic, Onit grew its employee base by 22% in 2020. The company’s leadership also took measures to support their employees’ well-being during these challenging times, offering help with perks such as additional personal days.
  • Global reach: Onit has a presence on five continents, with representation in Houston, Austin, Mountain View (California), Pune (India), Auckland (New Zealand), London (UK) and Kyiv (Ukraine).

How to Apply for a Job at One of the Best Places to Work in Houston

Are you interested in working at Onit? We’re always happy to hear from qualified candidates.

We also believe in having open transparency with our potential hires from the start. We encourage you to check us out on Glassdoor and LinkedIn, so you understand our culture and our people before you apply. If you think Onit might be a good fit, you should visit Onit Careers to view current job openings and apply.

For more insight on Onit, you can listen to the entire podcast here:

 

How Sales CLM with Contract AI Helps Business Development Automation

Posted on February 9, 2021 by - Artificial Intelligence, Business Process Management, Contract Lifecycle Management

It’s impossible to imagine any organization’s sales function without considering contracts. Sales operations professionals handle some of a company’s most value-generating activities: overseeing daily sales activity, meeting with major clients, drawing up sales reports, designing new and more effective sales strategies, and working to market and promote company products and services. 

None of those activities are possible if you can’t effectively manage your sales contracts and glean insights from them. Tools to manage contracts, including contract AI, are designed to ensure that sales operations and the VP of sales have a single point of truth for contracts. In addition, business development automation makes the sales Contract Lifecycle Management (CLM) process more efficient, and the entire sales function more effective. 

Contract AI Software in Sales

The sales function at any enterprise encompasses various duties, ranging from discrete contractual tasks to overarching strategy. On the contractual front, sales operations are responsible for many phases of contract lifecycle management, including: 

  • Creating requests for contracts 
  • Drafting contracts 
  • Monitoring the progress of those contracts 
  • Keeping contracts moving forward when things stall 
  • Approving contract terms 
  • Delivering contracts to customers for signature 

The sales function doesn’t end there. In addition to handling contracts daily, sales operations professionals find new opportunities to expand the organization’s client base and devise new and innovative ways to market products and services. It’s also responsible for setting specific critical enterprise goals and ensuring they’re met, including quarterly or annual sales and ongoing productivity goals. 

Underlying all sales functions, whether drafting a contract or setting the right sales goals for the entire company, is the expectation that the VP of sales and the sales operations team will continuously improve the sales team’s effectiveness and productivity. 

Technology is the key to ensuring continuous improvement. Sales CLM tools and contract AI empower sales operations professionals to better tackle both aspects of the job by making the contract process more efficient and effective from start to finish. In addition, AI–enabled sales management software helps create a central repository for the organization’s contract data. The central repository is a critical source of information for making informed decisions about sales goals and marketing strategies.

Finding the Right Sales CLM Solution and Contract AI Software

While every company and sales department is different, some common barriers prevent sales operations from performing effectively and efficiently. These include: 

  • Having little to no insight into where deals are, who’s responsible for them, and what the next steps are
  • Missing an easy way to keep deals moving forward
  • Not having mobile technology options to effectively handle work tasks in today’s on-the-go and remote working scenarios
  • Lacking self-service options that allow the various interested parties to create and manage that contract or request information directly.

A valuable sales CLM tool and contract AI software will remove barriers and help sales by: 

  • Closing deals faster with features such as self-service and contract AI that reviews, redlines and edits first-pass review within two minutes
  • Automating the contract request process to improve sales representative productivity 
  • Giving sales a real-time view of bottlenecks, where every contract is, and if the process is stalled 
  • Only showing the information you need when you need it, rather than burying you in a mountain of data irrelevant to what you’re doing at any given moment. Having immediate access to the correct data is critical to setting the right sales and productivity goals for your team and the entire organization. 

Speeding Up CLM for Sales – and Welcoming Revenue More Quickly

Sales operations professionals understand the role of contracts in doing their job right. However, they need the right CLM tools for sales to manage those contracts end-to-end. Onit’s CLM solution helps with business development automation for the entire contract management process, allowing for a more efficient sales function and better insight into sales data. Contact us today to learn more.

AI for Legal: Making Sense of the Hype

Posted on February 8, 2021 by - Enterprise Legal Management

John McCarthy, the computer scientist and “father of AI,” defined artificial intelligence as the science and engineering of making intelligent machines, especially intelligent computer programs.

When AI gets mentioned in the context of enterprise legal applications, it is usually referring to “machine learning.” In machine learning, systems learn from outcomes and decisions and improve with experience without being directly programmed to take certain actions or reach specific conclusions. These machines analyze data and discover patterns without significant human intervention, typically requiring only a training dataset.

Machine learning is often confused with rules-based automation, workflows based on pre-programmed “if this then that” algorithms. Legal buyers need to recognize the difference when looking to deploy AI within their departments. If the machine isn’t analyzing and learning from the data but is using pre-programmed, non-evolving rules to automate processes and outcomes, then it’s not AI.

Legal teams usually bring in machine learning to improve efficiency and productivity, as machines can perform tasks faster than humans, freeing legal counsel to do higher-value work. These applications include:

  • Legal Research: reviewing, tagging, and ranking documents relevant to a matter or eDiscovery, highlighting questionable ones that need human review.
  • ReviewAI: Identifying and flagging clauses for review, searching for missing clauses, and redlining in bulk and at speed.
  • Invoice Review: Coding, approving, rejecting, or flagging line items and invoices (where rules-based automation isn’t an option.)
  • Data Extraction: This can apply to invoices, contracts, documents, or any requirement where a mass of non-structured data must get organized and classified.
  • Litigation analytics: Analyzing trial data to predict outcomes of litigation.

GETTING THE MOST FROM MACHINE LEARNING

The above use cases and benefits can transform the legal profession. However, legal departments currently implementing an AI-powered legal solution may be disappointed by the true scope of these tools, especially if they are at the start of their digitalization journey. Buyers do not see the promised benefits and are beginning to question the hype.

The very nature of machine learning is that it needs data to deduce the patterns that help it to evolve and learn. This data doesn’t just need to be abundant in volume; it needs to be complete, accurate, fair, and free of bias. Improved accuracy vs. a human is a benefit often touted, but this is only the case if the data from which the machine is learning is accurate in the first place. Poor or insufficient data will mean the machine does not have enough data to learn from and will not fully deliver the anticipated outcomes and benefits.

Perhaps even more concerning, however, is that the machine will draw partial or incorrect conclusions from a deficient dataset and take the wrong action or reach the erroneous conclusion – thereby creating hidden risk. Ironically, AI can negatively impact productivity if a human must go back over the work, identify issues, and correct them. More severe, though, is if these incorrect conclusions result in damaging actions for the business, even litigation. The reliability of your machine learning needs to be a factor when accounting for legal risk, and legal teams need to understand their role in feeding machine learning tools with quality data and training to avoid these issues; as the saying goes, “you get out what you put in.”

If this sounds paranoid, some examples from other industries will help show why it is critical to be careful when deploying AI. In 2018, Amazon created a tool to review engineering CVs and flag the top ones for an interview. The intention was to automate a time-consuming process. To train the machine, they used the dataset of current Amazon engineering employees plus applications from the last ten years, which happened to be predominantly men. The machine “learned” that ‘more male’ candidates were the best for the role. Amazon soon ditched the tool. Poor data was also at the heart of IBM Watson’s failure to accurately diagnose and treat cancer patients. The data used to train the machine was hypothetical rather than real patient data and frequently gave poor advice. These examples demonstrate not only the importance of complete data for machine learning but the fact that it is hard to predict unexpected consequences before they happen.

The above examples demonstrate the importance of quality and unbiased data, even when the aims are straightforward. AI is not for complex legal work; it speeds up routine tasks, supports better decision-making, and sometimes takes actions based on those decisions. In fact, some of the best examples of AI deployment are where machine learning tools have been combined with rules-based systems to first identify and categorize data and then take defined steps based on that categorization.

MACHINE LEARNING AND E-BILLING

Spend management is a legal-specific application using rules-based automation and machine learning together. For example, Onit’s European legal spend management solution BusyLamp uses the following AI functionality for clients and/or law firms that prefer not to use LEDES files:

  • Data extraction: Pulling relevant information from PDF invoices, relieving smaller law firms from the burden of generating complex invoice files.
  • Invoice Reviews: Some law firms struggle to code invoices in a way that clients can understand. BusyLamp AI takes unstructured invoice data and auto-classifies every task to enable automated invoice review.
  • Legal Analytics: Unstructured invoice and matter data can be analyzed to enhance strategic decision-making.
  • Block Billing: English time narratives can be analyzed so that block billing, a practice that usually contravenes billing guidelines, can be identified.

IS AI RIGHT FOR YOUR LEGAL DEPARTMENT?

Using point solutions such as the e-billing example above allows legal departments to take advantage of machine learning benefits for gains in specific areas of legal operations. But machine learning is by no means critical to make efficiency and productivity gains; most BusyLamp clients start small and aim big by tackling the issues of collating knowledge, structuring, and cleansing their data sets, and then building automated workflows.

When you gather requirements for your next legal technology project, start by mapping out your current processes, roadblocks, and desired outcomes before looking at any specific technology tool. As you evaluate software vendors, you will discover various solutions and workflows to your problem, which may or may not involve AI.

Remember, you should never use AI for AI’s sake – it is rarely the silver bullet. Almost every legal technology tool uses rules-based (non-AI) automation to relieve the legal team of admin and mundane, repetitive tasks; this will be a fantastic starting point for most teams setting out on their digital journey.

There is no doubt that machine learning is playing a huge role in improving the productivity of the legal profession and will allow in-house teams to take a more pivotal, strategic role in their businesses. But as a profession familiar with risk mitigation, a degree of caution must be applied when looking to reach the machine learning “promised land.” Accurate, high quantities of data alongside a careful selection of technology tools will significantly reduce your exposure to these risks and help you make a success of your team’s digital transformation.

Because AI is so dependent on the data it receives, the real transformational tipping point will not be in using these solutions within the legal function alone but in the enterprise-wide application of machine learning tools. Imagine the insights and outcomes achieved by analyzing documents and data across an entire organization, not just the legal function. This is only achievable with integrated legal and enterprise tech tools and robust, extensive, consistent data.

The “power of AI” and its ability to change the legal profession are beyond question. However, it is essential to proceed with caution and lay the groundwork to ensure that your legal department sees the benefit of machine learning rather than learning that it has been sucked in by the AI hype machine.

Request a demo of BusyLamp eBilling.space today. 

The Future of the Legal Profession, AI and Legal Work

Posted on February 4, 2021 by - Artificial Intelligence, Business Process Management

The legal profession faced down seemingly endless changes this past year, and many people are understandably wondering what’s in store for the future. In a recent webinar sponsored by Onit and titled The Future of the Legal Profession, leading economist Daniel Susskind tackled exactly that question, offering insights on what changes the industry should expect in the future, what role technology and AI will play and much more.

A Tale of Two Futures

Susskind envisions two possible futures for the legal profession, both rooted in technology: one that’s simply a more efficient version of the current profession, and another in which technology actively displaces professionals.

In the first, today’s professionals continue to incorporate more technology to streamline and optimize the traditional ways they’ve worked, changing practices that may have been in place for several decades. In the second, technology isn’t just streamlining and optimizing traditional work practices, but fully replacing professionals with increasingly capable systems and machines. In the short term, these two divergent futures will develop in parallel. However, in the long term, Susskind expects the second future to dominate due to its greater efficiency and more effective problem-solving abilities.

How Technology Affects Professions

Professions evolved in modern society because no one was capable of doing everything, and therefore specialists – lawyers, doctors, educators, etc. – were needed to solve common challenges that people couldn’t solve on their own. Each profession became a gatekeeper for a unique body of knowledge.

Technology has been changing all that in recent years. Today, institutions are using technology to solve problems that were traditionally only solved by specific professionals. For example, in the case of law, three times as many disputes are resolved each year on remediation platforms without traditional lawyers than are filed in the legal system. Other technologies are similarly replacing hundreds of thousands of hours of traditionally billable time by addressing discrete legal tasks.

How Technology and AI Are Changing

There’s no finish line when it comes to technology. Today, technology is seeing exponential growth in prevalence, power, and capability, performing tasks that were once the sole province of humans. More and more people own devices, and both those devices and their owners are becoming increasingly connected. Over time, technology will only continue to improve.

Artificial intelligence has seen some of the most significant evolution. While AI once focused on copying human thinking and reasoning, today’s AI tools perform judgments that humans once exclusively performed and do so based on much larger volumes of data than humans could ever tackle.  (To see an example of how AI can quickly review, redline and edit all types of contracts including NDAs, MSAs, SOWs, purchase agreements, lease agreements, employment agreements, construction and sub-contracting agreements, visit here. You can also schedule a demo of Onit’s Review AI by filling out this quick form.)

The Future of Legal Work

We won’t be seeing robot lawyers any time soon, but we will see changes. Rather than eliminating entire jobs, technology will likely displace humans from particular tasks and activities, while making others more valuable and more important for humans to perform. Technology is a story not of mass unemployment, but of mass redeployment, changing the tasks and activities lawyers will be expected to perform in carrying out their work.

The Pandemic Effect

While the pandemic may have spurred recessions in some areas, recessions often lead to an increase in automation. Automation, in turn, tends to replace the tasks of middling-skilled workers, rather than lower-skilled or higher-skilled workers.

The pandemic has also created a unique incentive to automate work, since machines don’t have to worry about challenges like contagion or isolation. Some automation experiments necessitated by the pandemic are likely to become permanent fixtures of the profession, as there’s been a significant shift in the belief that most work needs to be performed face-to-face.

How This All Impacts You

Susskind closed with three pieces of advice for lawyers going forward:

  1. Explore new roles, skills and capabilities that might not be traditional in the profession.
  2. Learn from the pandemic. Understand what’s worked well and what hasn’t and apply that going forward.
  3. Imagine the future of the profession like a clean slate, figuring out how to solve problems in new and fundamentally different ways.

To learn more about Daniel Susskind, visit here.

To see how Onit’s AI solutions – including Precedent, ReviewAI and ExtractAI – schedule a demonstration here.

Coming Soon: InvoiceAI: AI for Legal Invoice Review

Posted on February 2, 2021 by - Company News and Events

Today, Onit kicked off its next phase of AI innovation at Legalweek(year) with the announcement of InvoiceAI, an AI-enabled legal invoice review offering for enterprise legal management. The offering, which will launch in May for both Onit and SimpleLegal, uses AI to create greater efficiencies in invoice review and allows general counsel and in-house counsel to focus on what they do best for their companies.

The invoice processing AI speaks to Onit’s founding principle: Help lawyers practice law more effectively. InvoiceAI eliminates tasks that aren’t related to practicing law – in this case, removing legal invoice review friction by relying on AI.

Onit leadership served as pioneers for legal e-billing, championing the Legal Electronic Data Exchange Standard (LEDES), the Uniform Task-Based Management System (UTBMS) and more. Now, that experience is taking legal invoice review to the next level with AI.

If you’re interested in learning more about Onit’s AI for legal invoice review, please speak with your account manager or email [email protected].

AI Innovation from Onit

When it launches in May, InvoiceAI will join three other AI offerings from Onit:

  • Precedent, Onit’s AI-powered business intelligence platform that automates and improves both legal and business processes for corporate legal departments, law firms, contract professionals, and procurement teams
  • ReviewAI, contract AI for pre-signature contract review that quickly and accurately reviews, redlines and edits all types of contracts in minutes.
  • ExtractAI, contract AI for post-signature contract management that extracts usable data from executed, legacy and third-party paper contracts.

You can schedule a demonstration of these three solutions by visiting this page.

The Sentinel Effect: 4 Ways Transparency Drives Better Business Outcomes

Posted on February 2, 2021 by - Legal Operations

Ever grabbed an extra cookie from the cookie jar as a kid because you knew no one was watching? Or maybe you skipped out on your last set of reps during a workout because, hey, who’s going to know? 

Sure, we’ve all been guilty of cutting corners when we know there are no consequences. But did you ever attempt to take that cookie with a parent in the kitchen? We’re guessing you probably wouldn’t risk losing precious screen time over one cookie. 

That reaction – not going for the cookie when your parent was right there – is commonly known as the “Sentinel Effect”. The tendency for one’s performance to improve when they know they are being monitored can be observed in all walks of life, both at home and on the job.

The simple act of monitoring – even without applying penalties – is proven to improve behavior. It’s a great passive management technique: show someone you’re monitoring them, and regardless of whether you are actually watching or not, performance will improve. 

This is especially true when managing outside counsel. Historically outside counsel has operated without the oversight – or even visibility – of their clients. That lack of transparency fostered a situation where not only were guidelines consistently ignored, but sloppy business practices were allowed to fester. 

But how do you transparently monitor outside counsel to create the Sentinel Effect? 

The answer is simple — data. All the answers you need are right there in your billing invoices; you just have to know how to use it to create not only a feeling of increased accountability but also to stoke that competitive drive within every lawyer. 

Armed with data, in-house teams have the power to:

1. Enhance Law Firm Relationships

Law firms are retained to act in the best legal interest of the clients, but when it comes to billing, firms are still businesses and can be self-serving. The relationship becomes one-sided as clients are often left as idle price-takers while firms receive hefty paydays. 

Having regular meetings with law firms fueled by a variety of quantitative and qualitative metrics, such as billing rates, discounts, and more, will lead to more effective, robust conversations about what’s working well or where adjustments might be needed. By letting the data do the talking, the conversation is much easier – and clients get better results from their firms. 

Simple practices such as incorporating firm report cards and quarterly business reviews to regularly discuss KPIs serve as a reminder to your law firms that you’re closely monitoring the value the relationship delivers. Nobody likes a “gotcha” moment, so these regular check-ins can help quickly correct firms’ course of action, leading them to become more disciplined in their billing practices and act as a strategic business partner.

2. Eliminate Inefficiencies

From overstaffing to partners handling associate-level tasks, and everything in between, efficiency isn’t always top of mind to law firms. In fact, there’s a strong possibility that the firm that billed the most hours in your panel may actually be the most inefficient.

Inflated invoices are often the byproduct of inefficiency. But transparency on key metrics, like average partner hours, matter duration, or cost can quickly highlight where inefficiencies rack up the cost of your matters.

Examining and discussing these key metrics with your firms regularly shows that you’re analyzing their efficiency and comparing them to other – potentially more efficient – firms. Your firms don’t want to lose your business, so expect a material boost in productivity and the elimination of inefficient practices. Once you show you’re serious about evaluating performance – and value efficiency – managing your outside counsel effectively will be much easier. By using data to set transparent expectations, you provide a clear roadmap to a stronger relationship. 

3. Influence Strategic Decisions

To effectively manage spend you need to think strategically — and to truly think strategically, you need data. Corporate legal departments are increasingly demanding transparency around everything from rates to work allocation to the diversity of timekeepers and more. But visibility isn’t the only thing that data provides.  

Armed with apples-to-apples comparisons and data-backed insights, corporate legal departments can take a more informed, strategic approach towards the major decisions that impact their department and the business. 

For example, as COVID-19 rapidly accelerated the need to optimize spend and cut costs, many corporate legal departments began to reevaluate their outside counsel spend. Many departments needed to quickly review their rates and obtain rate freezes and discounts from their firms. In turn, this forced competitive firms to follow suit. 

4. Drive Down Costs & Increase Savings

Pricing is arguably the most critical part of any business – product or service. By its very nature, pricing is complicated. “Pricing tricks” are a fact of life – that’s true if you’re pricing sneakers or legal services. 

Now, it’s no secret that law firms use “pricing tricks” – some more above-board than others – on both rates as well as in the manifestation of those rates; their invoices. From block billing to unapproved rate increases to footing the bill for printing, there’s no doubt you’ve fallen victim to unnecessary costs. But the good news is that you have the power to change this narrative. 

By leveraging data to track the performance of your panel firms, you can easily identify the common law firm antics driving up your spend and address them quickly. Using data to show a pattern will, almost miraculously, make certain antics disappear. You may have to negotiate or address other patterns by changing your billing guidelines. Nonetheless, data is your launchpad for not just identifying those antics, but for actioning solutions to them (clawbacks and markdowns, anyone?). 

It’s pretty clear that transparency in business – legal or otherwise – has the power to influence performance and drive better outcomes.

But, you don’t have to take our word for it! One of Bodhala’s clients, a major insurance carrier, was having issues with their panel firms consistently exceeding budget on corporate matters. Prior to starting a very large matter merger, the organization’s in-house team worked with Bodhala to create report cards to share with the top firms in their panel. After receiving a detailed analysis of their performance from the insurance carrier, each firm immediately brought down their budget projections significantly.

Without data, you’ll be hard-pressed to hold your law firms accountable for the quality of service you expect. Data sets the foundation for a successful, equitable partnership in which you receive the value you pay for. 

So, will you continue to turn your back on the cookie jar or will you leverage data to drive better business outcomes?

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Get in touch with our team of legal billing and data experts to find out how Bodhala can transform your legal department.

Harness the Power of AI in Operations Management for Corporate Legal Departments

Posted on January 28, 2021 by - Company News and Events, Contract Lifecycle Management

By now, businesses across all sectors recognize the benefits of legal AI in operations management – especially for processes such as contract management. Along with other technologies, AI is helping to reduce the financial pressure on operations teams and corporate legal departments who need to find ways to be more efficient. Particularly in the past year with the pandemic demands, there have been significant investments to decrease workloads for employees across businesses by streamlining things like workflow and approval processes. For example, this study found that contract AI in legal departments can increase efficiency by more than 50%.

In the first installment of our three-part blog and podcast series published earlier this month, we touched on AI’s ABCs. Now, we take a more in-depth look at some fantastic ways AI for operations is powering corporate legal departments. (You can find the podcast of this by scrolling down.)

Pushing Past the Buzz: Is It Really AI?

There’s no disputing that AI is a hot commodity now and a buzzword you hear often. AI in operations management and for legal teams is no exception. While you think your organization may be using it, you may be surprised. In reality, it can be challenging to identify, as AI in legal operations in day-to-day practice doesn’t always look like the images of AI we might have in our heads.

There are five ways to determine if you have an AI-driven system in place.

  1. Use of an interactive system – A fundamental cornerstone of AI is the ability to interact with your system more conversationally through the concept of a virtual agent.
  2. A wizard powered by learning to guide users – AI-enabled wizards lead users to the right workflows and tools, such as contract templates. This is based on learning from previous contract requests to offer more interactive guidance for your staff.
  3. Identification – Semantic analysis by AI can find patterns in related words relevant to an issue and then applies appropriate tags. This AI enabled semantic analysis is frequently used to identify issues in contracts, for example.
  4. Advanced analytics – AI builds off the identification process and allows you to utilize the identified terms very quickly by providing actionable recommendations for tasks.
  5. Robotic Process Automation (RPA) – RPA can be used for approval of changes, not only in workflow but to help your system streamline the approval process by learning from decisions made in prior cases. Essentially, you’re changing the workflow based on past learning and providing recommendations to approvers based on previous actions.

Corporate legal departments vary widely in their current technology levels, so you may not see all of these hallmarks in your organization. Nonetheless, if you can do any (or all) of the things listed above, you’re currently using AI. The next question is how to ensure you’re fully taking advantage of it.

The Benefits of AI in Legal Operations

AI has significant impacts on lawyer productivity. Onit recently conducted a study of legal AI contract review software to see how it affected in-house lawyers’ productivity. The results showed that new users were immediately 34% more efficient and 51.5% more productive. Team leaders could reallocate 15% of their time from contract work and team management to higher-value activities if they use AI in operations.

Consider those results in the context of a typical midsize company that has 28 lawyers and reviews 4,850 contracts annually. With 51.5% more productivity, that same team of 28 lawyers could process 2,498 additional contracts each year. That’s the equivalent of adding nine lawyers to the team. The additional capacity could also reduce costs and free up lawyers to perform higher-value functions to support the business.

The benefits of legal AI don’t stop with productivity. Legal departments must have access to data, and AI for operations allows departments to combine data from all corporate data sources. AI can also flag suspect transactions or questionable third-party relationships and quickly assess their risk level. Having a value chain of data with an intelligence layer around it is essential. Being able to connect that intelligence layer to your legal operations is crucial.

Listen to the Podcast Now: Contract AI in Legal Operations

For a more in-depth discussion of AI enabled contract management and its importance for legal operations, you can listen to the entire podcast interview below.

In our third and final installment of this blog series coming next week, we’ll dive into some of the most useful forms of AI being used in business today.