The impact of automation and legaltech on lawyers and law firms.

Juan Pablo Dama
Apr 17 · 8 min read

A few weeks ago, I had dinner with a group of friends, most of them lawyers. During the conversation, I asked them about the impact of automation technologies on their profession. Naturally, their first reaction was that their job couldn´t be done by robots and that automation wouldn´t affect them.

It’s true that there are some characteristics of law, like being highly regulated, courts being government institutions and the tight controls on lawyers and law firms, that make- any change in law harder than in other areas or professions.

However, the application of artificial intelligence and automation technologies in law have already started. There are already over a thousand legaltech start-ups worldwide and according to Tracxn, in 2017 £172m were invested across 61 legaltech firms.

As automation continues evolving, the impact on the legal — multi-billion dollar- business services could be enormous.

Which legal tasks can be automated?

An example of automation applied to law that I mentioned to my lawyer friends was a recent study on Non-Disclosure Agreements (NDAs). LawGeex artificial intelligence algorithm challenged lawyers from firms such as Goldman Sachs, Cisco and Alston & Bird to review the risks contained in five NDAs. The result of the study was that LawGeex tool achieved an accuracy of 94% and reviewed the documents in just 26 seconds. In average, the group of 20 lawyers achieved an accuracy of 85% and reviewed the documents in 92 minutes.

This huge efficiency is a good illustration of one of the main outcomes of automation, which is that it allows performing tasks in volumes and speeds that humans will never achieve.

Here is a list of tools that are automating legal tasks and processes:

  • Document review and analysis: Most of the legaltech start-ups have focused on improving the management of documents and contracts for due diligence, M&A, compliance and insurance. These tools, rapidly review and analyse contracts (unstructured data) using technology. In this case machine learning and neuro-linguistic programming. More advanced systems, like Luminance, have pattern recognition algorithms that allow the system to understand by content and context.
  • Analytics and research: These types of tools mine from millions of pages of legal information to provide strategic insights on judges, jury and lawyers. Users can ask the tool and it will review the relevant law stored in its systems, gather evidence, draw interferences and return highly relevant evidence-based answers. Same as other machine learning tools, the programmes continuously learn from its usage and brings better results over time. It allows law firms to predict the behaviours and results that different legal strategies will produce, enabling them to win cases and close businesses.
  • Blockchain / Smart Contracts: It’s creating contracts with self-executing elements without the need for intermediaries. These are dynamic contracts that autonomously manage themselves after the parties have reached an initial agreement. Smart Contracts are trackable, irreversible and provide security that is superior to traditional contracts.
  • Contract Platforms: Platforms like Contract Express from Thomson Reuters generate- standard legal documents from automated forms. These forms are created automatically from the company’s own templates. Also, there are other platforms that improve the contract drafting process by allowing live collaboration on legal documents with colleagues and advisors, and then, to negotiate directly in the platform with counterparties. Parties can monitor push-backs in clauses, track revenue-hitting terms and compare individual negotiators.
  • Contracting Platforms: Are systems that allow lawyers, whether in a law firm or corporate, to greatly speed up and improve the contract (and other legal documents) generation and completion process. Often included in these are automated improvements to the negotiation phase, as well as a layer of data extraction that allows the user to gain better insights into the contracting process and its outputs. Examples of Contracting Platforms are Outlaw and Ironclad.
  • Time analysis: These types of tools are used to understand and predict legal costs. They use neuro-linguistic programming and machine learning that monitors historical and current users’ behavioural data. They allow in-house legal teams to monitor in real time all their external legal expenditure, including work-in-progress. It’s also suitable for law firms, it allows them to forecast complex litigation costs accurately.
  • Document management: Are tools that combine different automation technologies to improve documents workflow — deal management, signature, minutes, project management, data room and analytics.
  • Patents: Are tools to automate the process of patent drafting and patent preparation. Probably the best one is Lex Machina, which can predict the probability of success in a US patent litigation more accurately than litigators. Also, there are tools like XLPAT that allows users to search prior art for patents within minutes.
  • Lawbots: Are AI applications used to automate specific legal tasks like the design and creation of electronic and computer-assisted legal research. Lawbots are different from chatbot systems. Chatbot systems like DoNotPay or are not AI, they are just step-by-step guides to complete a legal process.
  • Data Room: These tools apply machine learning and dashboards to show the user key information from the documents stored in a data room. It can automatically classify document types, detect languages, currencies, governing laws and detect or extract provisions and data points from the documents stored in the repository.

It’s true that there are some characteristics of law, like being highly regulated, courts being government institutions and the tight controls on lawyers and law firms, that make- any change in law harder than in other areas or professions.

Who are the main legaltech players?

It’s a market dominated by two incumbents, LexisNexis and Thomson Reuters.

LexisNexis — tries to cover as much legal automation variables as possible with its four products:

- Lexis Advance applies AI, machine learning and visualization technologies to analyse data.

- Context is the result of the integration of Ravel (a recent acquisition) and Lexis Advance technologies. It analyses 100 motion types and examines millions of case law documents to reveal language relevant to cases.

- Lex Machina anticipates behaviours and outcomes with quantitative data on case timing, resolution and damages.

- Intelligize (another recent acquisition) helps to build stronger deals and strengthen negotiation positions by benchmarking what others are disclosing.

Thomson Reuters’s Westlaw Edge platform is mainly a legal research service that uses historical attorney-edited annotations to deliver answers and gain insights. It also has services covering legal forms and drafting, case strategy and integrated data and solutions.

Other important legaltech players are: ROSS Intelligence (an on-demand research associate tool), Modria (an online dispute resolution tool), Neota Logic (a document management automation tool), Casetext (legal research tool), Gavelytics (judicial analytics tool) and Kira (a document review and analysis tool).

What’s the future of lawyers and legal services?

The result of automation technology applied to legal services will impact mainly in four areas:

1. Governmental institutions

2. Law firms’ structure and business model

3. Number of legal jobs

4. Nature of legal jobs.

1. Governmental Institutions:

In 2015, the British government announced an ambitious six-year plan to modernize and fully digitalize courts. With an investment of over £1bn, it will allow a large number of civil disputes to be resolved online.

With fully digitalized courts, lawyers will rarely be required to physically appear in courtrooms. Also, it will make it easier and cheaper for people to claim, so it’s very likely to forecast an increase in the number of disputes.

Today, modest claims like parking fines or compensations for delayed flights, are not worth to start an expensive, bureaucratic and time-consuming legal process.

Legal institutions should consider using a system similar to eBay’s Online Dispute Resolution (ODR) techniques. eBays handles over 60m disputes per year (which would be absolutely impossible to resolve via conventional courts) by offering two services, a free web-based forum which allows users to attempt to resolve their differences on their own, or the use of a professional mediator for $15. The whole resolution process generally takes 10 days.

2. Law firms’ structure and business model:

The structure of law firms and three-quarters of all lawyer’s work and tasks performed haven’t changed much for the past 100 years. It could vary depending on the size of the firm, but it generally doesn’t differ much from the intern-associate-partner formula. Typically, law firms offer a bespoke service to clients and charge them a fee per hour depending on the seniority of the lawyer involved.

The amount of legal work that requires bespoke treatment is generally — way less than what law firms actually offer to their clients. Usually, lawyers draft a new contract or document from scratch when it would be more convenient to just standardize or automate that part, or the whole process. Historically, law firms haven’t been motivated in optimizing their operations because they lived in a world where ‘time is money’ and the more hours they dedicate to a task, the higher the law firm´s income-. Disregarding the demotivating and dehumanising impact of repetitive and intellectually null tasks that highly qualified individuals have to spend time doing.

Law firms will need to redefine their business model and manage to reduce their fees. Legal tasks traditionally performed and monopolized by lawyers are starting to be displaced by feasible alternatives. Clients are not willing to pay expensive legal services for work that can be done by non-lawyers supported by automated systems and standardized processes.

Also, marketplaces like UpWork, where users can compare fees and reputation, will become more popular. Naturally, freelance lawyers charge lower fees than traditional law firms, and — thanks to AI they will be able to use their time working on parts of the job that are more analytical and intellectually challenging.

3. Number of Legal Jobs:

Typically, the tasks performed by junior roles are low-skilled and repetitive. As described previously, many of the legaltech start-ups are doing a great job on automating these types of tasks, and overtime junior and generalist roles will become obsolete.

Brian Tamanaha, in his book Failing Law Schools, describes the issue thousands of law graduates are facing in the US. He points out that the out-of-pocket costs to obtain a law degree is around $200,000 and the average law school graduate’s debt is over $100,000, with the scarce jobs offering starting salaries -. On top of this, he mentions that there are only 25,000 new job openings for young lawyers while law schools are producing 45,000 graduates per year.

This situation will be even worst once law firms completely embrace automation and stop hiring graduates. This has a negative impact on youth employment and access to jobs.

4. Nature of Legal Jobs:

The adoption of technology in law is a process that has started. Initially, it is impacting junior roles, legal clerks and other legal support functions, but will completely change the way lawyers work and will convert them to become data-driven.

A large proportion of legal tasks won’t need to be performed by experts in law. Instead, they will need professionals who will need to be fluent in technology and data management, able to define and integrate automated systems to perform legal tasks. They will spend more time managing and supervising the system than in specific legal related tasks. There is a proportion of complex tasks that will require expert lawyers to take care of them, like tasks that require human interaction, negotiation, and emotional intelligence.

As automation continues evolving, the impact on the legal — multi-billion dollar- business services could be enormous.

When will AI have a noticeable impact on the legal profession?

Most of the automation tools mentioned above are relatively new and haven’t been completely integrated into law firms and in-house legal departments.

Whilst this is slowly happening, the process of law firms embracing automation won’t be as fast as it has been in other areas like accounting or HR, making it hard to say exactly when AI will have a noticeable impact. However, there is little doubt that by 2030 the legal profession will look completely different from now.


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Juan Pablo Dama

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