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How AI is disrupting the legal tech industry

(Image credit: Image Credit: Razum / Shutterstock)

Although artificial intelligence (AI) has been around for decades, the industry has seen a recent resurgence. According to a report from PwC and CB Insights, AI investment in the US resulted in a 36 per cent compounded annual growth rate (CAGR) between 2013 and 2018. This jump in AI spending was more pronounced in 2018, increasing 72 per cent from the year prior.

As momentum grows, intelligent software is permeating a diverse range of industries. The pursuit of operational efficiency and resulting cost savings remain primary drivers of AI adoption. In industries known for their paper-heavy processes, AI functionality is particularly appealing. Reflecting this reality, legal technology (legal tech) applications are increasing steadily.

According to Zion Market Research, the global legal tech AI market was valued at approximately $3.25 billion in 2018. By 2026, the industry is expected to generate around $37.9 billion, reflecting a CAGR of 36 per cent over seven years. But why exactly are legal professionals adopting AI with such enthusiasm?

To answer this question, it’s important to explore the taxonomy of AI, potential legal applications, and the key to successful implementation.

As increasingly complex AI solutions emerge, the technology continues to capture imaginations across the legal community. AI has become a catalyst for change within the legal ecosystem. And as platforms become more sophisticated, companies have begun to tap into ever-expanding automation and scalability.

Legal professionals around the globe conduct exhaustive legal research on behalf of their clients. This fact-finding mission is tedious and time-consuming, requiring a thorough analysis of prior cases. AI tools can help ease the administrative burden of this process by streamlining the collection of background information. For instance, an AI tool might scour a database of previous cases, returning only relevant information.

As one of the more advanced applications of legal tech AI, predicting legal outcomes is much less explored but holds immense potential. Unlike the human mind, AI can store and analyse vast catalogues of legal data, providing valuable insights in real-time. This functionality can help determine the chances of winning a case, optimising decision-making and resource allocation.

Contract management

Law offices spend a lot of time reviewing contracts for their clients. This process, meant to identify contractual risks and issues, requires intense scrutiny. AI tools can help streamline this undertaking by collectively or independently assessing contracts based on a pre-built AI model.

Intellectual property law

According to the World Intellectual Property Organizations (WIPO), there are many factors driving the use of AI in the administration of intellectual property systems. However, a lack of human capacity is arguably the most prominent. As of 2016, 3.1 million patent applications, 7 million trademark applications, and 963,000 industrial applications (across 1.2 million designs) were filed around the world.

In response, entities like WIPO have introduced solutions such as AI-powered image search tools for trademarks and an International Patent Classification (IPC) system built on neural network technology.

Implementing LegalTech AI

Although there are many benefits to implementing legal tech AI, law enterprises must ensure their efforts are focused and grounded in reality. Taking the time to develop a comprehensive plan is likely to produce better outcomes. In creating this plan, there are several vital considerations legal professionals should assess.

Obtain quality data

To determine the appropriateness of AI tools, legal service providers must first determine what data-driven process requires improvement. Quality data will form the backbone of any intelligent system, and understanding how this data facilitates meaningful AI outputs is crucial.

Many AI applications rely on an initial data collection process that highlights the state of data and how it will guide AI implementations. For instance, it might be necessary to clean up existing data while also introducing processes that ensure future data-generating activities yield clean, reliable data. Those companies that can successfully interpret this high-quality, proprietary data will have an inherent advantage over industry incumbents.

Leverage industry knowledge

As the saying goes, knowledge is power, and in this case, it's vital to the success of any legal tech AI platform. Although AI technology and its software are powerful, there's no substitute for human specialisations and accumulated experience.

AI tools must be built with the end-user in mind to ensure optimal results. In the world of law, only legal professionals will have the real-world insights necessary to generate contextualised AI outputs. However, lawyers aren't data scientists or software developers, and ongoing collaboration across teams is also required to transform data into usable models.

Focus on enhancement, not replacement

Recall that quality data is crucial to the development of effective AI solutions. Incomplete or erroneous inputs can generate unintended consequences, making predictions or providing outputs with varying degrees of certainty.

Because lawyers operate with high levels of precision, the inherent risks of trusting machine outputs remain too risky for some. That said, it's important to note that AI is not meant to replace lawyers, it's intended to enhance their natural abilities. Human judgments and experience will remain a crucial component of any intelligent platform.

As legal professionals around the world continue to optimise their business models, AI offers an opportunity to lower costs and improve outcomes. According to Deloitte, law firms will have to implement new talent strategies by 2020, ushering in a new approach to legacy processes. And if forecasts are correct, this transition is set to automate 100,000 legal roles by 2036.

This reality is driven by the democratisation of legal services as a result of AI integrations. The movement is poised to lower the costs associated with corporate transactions, legal research, IP transactions, and related services. As such, law firms will benefit from a growing ability to deliver high-value, strategic services while leveraging the ability of AI to execute lower value tasks.

In light of these predictions, it appears that now is the time for law firms to embrace AI-enabled applications. For those that don't, there's a genuine risk of being left in the past.

Derek Chau, Partner, Acorn Pacific Ventures