AI and Technology systems innovation (AI-tech) has become a beacon of hope of what can be achieved by improved use of data science and machine learning to cope with a number of principal legal tasks in the judicial system.

AI and Technology systems innovation (AI-tech) has become a beacon of hope of what can be achieved by improved use of data science and machine learning to cope with a number of principal legal tasks in the judicial system.  Players in the legal field want to know how to make necessary improvements in the use of technologies and how it may be used to reshape their business strategies.

To help answer these questions, I have compiled a list of some of the generic uses of data science use cases which has the potential to have an impact on the legal field.  They cover diverse aspects from data management to policy changes, but the common thing for them is the huge prospects to enhance the use of AI tech in the legal field.

Automating trial management

Person’s within the legal field spend a great deal of time positioning themselves for trials and activities to manage client output and to prioritise activities within their organisations.  Digital systems that monitor these types of activities often use historical data to get started, then by learning from human decisions can use this data going forward to improve accuracy continually, also improve efficiency, and which in turn increases firm productivity.

Trial management is an essential area for law firms and judges, and AI-tech can assist in strategically driving decisions concerning case management.  The approaches to handling case management may change significantly over the upcoming years due to AI-tech, transforming the nature of the legal profession.  As entities within the legal field drive toward automating workflow, document and timesheet management to ensure each activity in the life of a matter is accurately completed, billed, audited and tracked.

Managing risk

This digital system accuracy can also be used to manage risk.  There are many origins which give rise to risk from client relations, professional responsibilities (including malpractice, conflicts, records, and litigation support), and professional development risks.[1]  Also, risk origins often differ in importance and possible losses.  AI – tech and machine learning training on the huge amount of client data can be to use to mitigate risk by identifying, prioritizing, and monitoring risk.  This can be done by using a practice management or legal management tool  that enhances the risk recording models and assures cost efficiency and productivity within the legal field.

Another way in which risk can be managed is handling the completion of repetitive transactions, for example, the JP Morgan learning system for COntract INtelligence(COIN).[2] COIN analyses a document in seconds, with fewer errors than humans, resulting in considerable cost savings for client.  To date, it has replaced hundreds of thousands of human lawyer – hours in interpreting commercial loan agreements.[3]

Managing reputation

Firms realise that one of the critical steps to being competitive in today’s market is to effectively engage with consumers through personalised relationships with their clients.  It’s well known that, by far, “the most significant risk to a professional services firm is to its reputation; that is its ultimate asset”.

The idea in using AI-tech in managing reputation is to analyse digital client experiences and, modify it by taking into account the client’s interests and networking preferences.[4]  AI-tech can assist in making significant improvements in understanding human language and emotion, through data scientists using AI models that study the consumers’ behaviour and discover situations where customers may require legal advice.[5]  The combined use of predictive analytic tools and advanced digital delivery mode can assist the client to garner legal solutions at the most convenient time and suggesting personalising offerings based on the matters, common social-demographic trends, location, and other preferences.

Policy Changes

One of the key changes that AI can bring is changes in policy that advances a duty on technology competence, a requirement that arises from American jurisprudence.  The duty on technology competence, states “that those within the legal profession must maintain the requisite knowledge and skill, that lawyers should keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology, engage in continuing study and education and comply with all continuing legal education requirements to which the lawyer is subject”. [6] The duty of competence aims to support AI-tech innovation by necessitating lawyers to be aware of the benefits and risks of emerging technologies that can be used to deliver legal services as well as enhance their client delivery.  The rate at which technology is advancing influences a lawyers understanding of how to use an available technology and has high potential impact on the legal field.

In South Africa, under the Office of the Chief Justice (OCJ), the judicial governing body has forwarded an introduction of  the implementation of CaseLines digital system aimed at implementing paperless digital courtrooms in South Africa.[7]  CaseLines,  tools allow the creation and presentation of a fully digital bundle including multi-media evidence; collaboration tools for enhanced pre-trial preparation and secure role validated video conferencing for virtual hearings.[8]  This incredible digital system will surely lead to  a duty of competence on legal practioners.


For legal institutions, the usage of data science techniques provides a huge opportunity to reinvent the field.  There are vast amounts of continuously changing data concerning the legal field, which creates a necessity for use of machine learning and AI tools into various aspects of the legal field.[9]  Importantly to transform the judiciary there must be a vast drive to support AI and technology systems innovation.

This article outlined just a few data science use cases in the legal sector, but there exists a great deal more that also may deserve to be mentioned.  If you have any further ideas and if you seek more good, clear precise advice, speak to us.

[1] Cunningham, D (2009),  An overview of law firm risk management.( Chapter 1)  Available on https://www.slideshare.net/DaveCunningham/risk-management-for-law-firms-chapter-1-ark-2009-by-dave-cunningham. Last accessed on 2019/06/21

[2] Business Insider JPMorgan takes AI use to the next level –Available on  https://www.businessinsider.com/jpmorgan-takes-ai-use-to-the-next-level-2017-8?IR=T. Last accessed on 2019/06/21

[3] Ibid

[4] See Theil, W The Role Of AI In Customer Experience Available on  https://www.pointillist.com/blog/role-of-ai-in-customer-experience/ Last accessed on 2019/06/21

[5] Ibid

[6] The duty of technology  competence as framed in ABA Model Rules of Professional Conduct Rule 1.1, Comment 8 in 2012 Available on https://www.americanbar.org/groups/professional_responsibility/publications/model_rules_of_professional_conduct/rule_1_1_competence/comment_on_rule_1_1/ . For further insight see Tashea, J and Economou, N Be competent in AI before adopting, integrating it into your practice. Published on 23 April 2019 Available on http://www.abajournal.com/lawscribbler/article/before-lawyers-can-ethically-adopt-and-integrate-ai-into-their-practices-they-must-first-be-competent

[7] South African OCJ implements digital justice system – Available on https://www.bizcommunity.com/Article/196/546/190753.html

[8] Ibid,

[9] See link for comprehensive examples of AI-tech use in legal field Available on https://emerj.com/ai-sector-overviews/ai-in-law-legal-practice-current-applications/

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