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What to consider when integrating AI into legal

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Over the past two years Webber Wentzel has explored a number of artificial intelligence (AI) platforms related to the delivery of legal services.

By Celia Pienaar, lead project manager at Webber Wentzel

Many people believe that automation is a threat to job security with predictions by Accenture stating that that 35% of jobs in South Africa (equating to 5.7 million jobs) are currently at risk of total automation.

Our experience of AI and automation is that it is not something to be feared, but rather embraced – it’s a win for us and a win for our clients. It frees up our time and allows us to focus on higher value and more complex matters and our clients benefit through reduced costs associated with commoditised tasks. In many senses, these platforms will not necessarily create ‘robot lawyers’ but rather take the robot out of lawyers.

Also, new legal technology has brought about new skills requirements and in the legal industry we are seeing new roles taking shape such as legal assistants, legal technologists and legal project managers; all playing a major role in the implementation of and service delivery through AI platforms. So, it’s fairly likely that new types of jobs may be created within the legal services industry.

Based on our experience, we set out below some useful considerations companies should consider when exploring partnering with one or more AI driven platforms:

* Use of AI systems by in-house legal teams – While some of the in-house team’s work can be automated or streamlined through the use of suitable legal technology and AI platforms, one has to bear in mind the high costs of these platforms and the skills required to fine-tune its application and maintain its learnings. The value add of having a suitable platform or panel of platforms procured by law firms instead of in-house teams lies in the fact that the specialist legal advisors will be training the systems based on their broad experience, and platform investment costs will be shared amongst a group of clients.

* Legal project management – Due to these platforms’ immense learning capabilities, legal teams need to carefully manage its gradual knowledge building, and follow a methodical approach to implementation on each matter. As an example, platforms often have the ability to reanalyse vast sets of documents based on further training, so one must be careful to maintain electronic audit trails of decision making processes and change requests.

* High costs of machine learning legal technology – In practice, the application of AI platforms is still expensive and therefore not suitable to all matters. That said, we expect costs to decrease considerably over the next two years as more AI providers enter the market, making it more affordable and beneficial to use.


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