AI-powered
solutions rely on the above technologies discussed. These solutions are very
critical to the legal industry today. Micheal Mills, in his article, Artificial
intelligence in law: The stage of play 2016, remarked that a search on
‘artificial intelligence in law’ produced 86,400 results from just the news
section of Google’s vast index. Subsequently, 32.8 million results from the web
and from videos, almost 261,000. Again, according to Wolters Kluwer’s 2020
Future Ready Lawyer Survey, 58% of legal departments expect AI to affect their
organization over the next three years, with 82% of corporate legal departments
expecting a greater use of technology to improve productivity over the course
of the next three years.
Indicatively,
AI-powered solutions have permeated almost every part of the legal service
delivery industry today, helping law firms to be more efficient, and providing
quality service at great speed and accuracy. Some of these AI-powered solutions
are Luminance, Lex Machina, Relativity, Contract pod AI, Clarilis, Premonition,
Thomson Reuters, Clide and Co, App4Legal, Kira, Leverton, eBravia, COIN by JP
Morgan, ThoughtRiver, LawGeex, Legal Robot, Lawdroid, and Ross Intelligence to
name a few.
Law
firms naturally have some constraints on resources in most cases. Resources
here would suffice for the availability of lawyers, the financial strength of
the firm, and the time available per count of lawyers. It may also further
include other logistical needs like office space for the library et al. For a
law firm, therefore, to promote efficiency in its organization with no
resourcing needs requires the firm to make good use of its resources,
especially lawyers and time. An efficient law firm promoting efficiency will be
profitable. I will recommend AI-powered solutions that provide the following
services, i.e., legal research, contract review and management, document
review, predicting legal outcomes, and more.
AI-powered
solutions for firms to promote efficiency with no resource issues will include
Luminance AI, which provides for automated contract drafting, negotiation, and
review, end-to-end eDiscovery (from investigation to litigation), and the
spectrum of contract review projects. These legal services are very
time-consuming tasks that most times impact service delivery. Luminance AI,
using Natural language processing and machine learning as discussed previously
reads, and forms some conceptual understanding of the documents fed to it in
any language to augment tasks ranging from a review of initial contracts to
automatically flagging anomalies within the contract, and further bringing into
the limelight areas of non-compliance needing to be remedied.
It
can hierarchically assign workflows and perform some low-level task automation,
freeing up critical resources for strategy formulation, analysis, and advisory
roles. The amalgamation of all these leads to efficiency and productivity.
Luminance AI applies Natural Language Processing and pattern recognition,
combining both supervised and unsupervised machine learning. Using unsupervised
learning, its e-discovery abilities aid litigators in identifying hidden and
incontrovertible evidence amongst mountains of irrelevant materials. The more
lawyers use this AI-Powered solution, the more they can understand such
patterns of lawyers, thus becoming more intelligent and become customized for
each lawyer’s needs. Luminance has now seen and analyzed over 100 million
documents in over 80 languages across hugely diverse fields of law, from
non-potential risks, anomalies, or contentious issues are surfaced when using
Luminance’s AI to draft and review documents. Thus, the attribute of this
solution promotes efficiency.
Second,
Ross Intelligence is another AI-powered solution suitable for such an
organization. Diligent legal research is very critical to a law firm’s
efficient utilization of its resources. The valuable attribute that goes into
thorough research can be very daunting for law firms. Similarly, Ross’ intelligence
applies natural language processing to ask relevant questions and receive
information on related case laws and other tertiary resources. Most firms using
Ross Intelligence have seen significant improvement in their efficiency
ratings. Baker Hostetler is an example, having used the software to work on 27
terabytes of data, with a Forbes report describing Ross’ function in the law
firm’s operations: Ross will be able to quickly respond to questions after
searching through billions of documents. Using NLP and machine learning, it
performs the following tasks, i.e., question-based search, finding similar
language constructions, document analysis to ensure arguments are bulletproof,
question-focused case overviews, and case treatments to avoid bad laws.
ThoughtRiver
AI is another solution that leads to efficiency in law firms. Some use cases
are in contract negotiations, contract review, and contract self-service. Using
Artificial intelligence produces some level of visualization of potential risks
through the scanning and interpretation of written contracts used in commercial
risk assessments. This solution decentralizes contract review and negotiations,
aiding firms to do more with less, thus increasing efficiency. It also helps
reduce risk and increases compliance against the same legal policies. Lawyers
can therefore do more in less time, by delegating transactional work to the
business and actively reducing the need to engage with outside counsel. Also,
it is estimated that about 50% savings are made on time for reviewing and
approving contracts and because lawyers can now do more, as well as sales and
procurement teams are enabled to review contracts themselves, a lot more
business is executed at a reduced cost.
Premonition
AI is another AI-powered solution that focuses on legal analytics and courtroom
data insights. Using both supervised and unsupervised learning, as well as deep
learning technologies, it deeply on real-time court monitoring with a
far-reaching coverage larger than lexiNexis, Bloomberg, and Thomson Reuters
combined. It has advanced filtering capabilities of reading over 50,000 pages
in under a second. To assign lawyers to specific cases, Premonition AI aids in
accessing the lawyers based on their litigation experience, case types, performance
(regarding their overall, case type, judge, and client) as well as duration on
the same metrics. It, therefore, allows for the efficient allocation of
resources available to the firm. It also performs predictive analytics using
machine learning and deep learning tools to comb through the millions of
volumes of cases cutting across the hierarchy of the courts and judges, to
arrive at near accurate predictions on new cases, provide counsel and decide
strategies for case management. Decisions arrived at based on its algorithms
are data-driven and cut across tons of millions of data records, beyond a
lawyer’s own biases and anecdotal experiences. This leads to efficiency within
the organization.
Author: Ing. Bernard Lemawu, BSc Elect Eng,MBA,LLB,LLM Cand. | Member, Institute of ICT Professionals Ghana
For comments, contact author ghwritesblog@gmail.com
Source: www.iipgh.org
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