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Legal AI tools and AI assistants: must-have for legal professionals

How legal-focused generative AI tools help law firms and legal departments 

Artificial intelligence (AI) is rapidly becoming an essential tool for many professionals across various industry sectors, and the legal profession is no different.  

By automating numerous repetitive, mundane tasks and replacing outdated ways of working, legal teams can experience the power of generative AI tools that feel like reliable AI assistants. 

Jump to:

icon-orange abcs How is AI used in the legal profession? 


AI for faster data synthesis and analysis 


icon-speaking bubble More efficient legal research and drafting 


Streamlined M&A due diligence 


Improved knowledge management 


Enhanced onboarding and learning 


Plain-language prompting to navigate complexity 


icon-business buildings Trustworthy security and privacy


 

AI is a simulation of human intelligence by a machine, and this opens up a whole world of possibilities. Generative AI can assist with document processing and classification for a wide range of matters, including due diligence, document and contract review, compliance, contract lifecycle management, knowledge management, and deal analysis.  

By automating these tasks using intelligent technology, significant workflow benefits can be achieved, particularly with improved efficiency and productivity as well as greater accuracy.   

The use of AI at law firms has transitioned from a mere desire to an essential requirement. It is changing the way we do business, in much the same way as email did in the 1990s. As digital transformation continues to advance, legal AI will become ubiquitous and an indispensable assistant to practically every lawyer and legal professional, freeing up time for tasks that add greater value such as thinking and advising. 

“Legal generative AI is supposed to augment what a lawyer does. It’s not going to do legal reasoning, not going to do case strategy. What it’s supposed to do is do repeatable rote tasks much more quickly and efficiently.” 

– Zach Warren, Manager, Technology and Innovation, Thomson Reuters Institute   

 


Report thumbnail with title — A game-changing shift, What AI means for modern lawyers today Special Report 

A game-changing shift: What AI means for modern lawyers today 

Read the report 


 

AI for faster data synthesis and analysis  

Creating, reviewing, and sending various documents forms a large part of a lawyer’s daily tasks. While important, these are repetitive and manual processes and are typically prone to human error, which can introduce an unnecessary element of risk. Legal AI tools backed by expert human oversight give you a competitive edge by improving accuracy and thus reducing risk. 

With the power of AI in your legal tech tools, you can sort files rapidly and seamlessly without needing to manually examine them. The range of assistance offered by legal-focused generative AI improves the law firm’s or in-house legal department’s output by facilitating the legal professional’s ability to apply their higher-level expertise to the work at hand. 

 

Consider the value of AI-enhanced legal research technology. 

Generative AI provides a jumpstart on legal research by reducing the time legal professionals must spend sifting through and summarising content. These tools can produce in moments an informative version of research that would have previously taken hours or days.  

Lawyers can then apply their expertise to refining the results to ensure that the research output is high quality, thorough, and accurate.  

“For any of the tasks that lawyers do on a regular basis or that administrative professionals supporting the legal industry do on a regular basis, this technology allows them to do those things faster and to create a starting point much earlier in the process.”  

– Zena Applebaum, Global VP, Product Marketing for Research Products for Thomson Reuters 

 

Streamlined M&A due diligence  

M&A due diligence is a tedious task that limits your time and ability to innovate and creatively problem-solve. Using legal AI tools for analysis and review of documents saves time and allows you to focus on more valuable pursuits, which facilitates enhanced creativity and allows you to focus exclusively on the tasks that only a person can handle – the job you were trained to do and the job you are passionate about.   

 

Improved knowledge management 

Generative AI can help legal teams stay organised and share information via cross-functional tools. Better and faster methods of saving, indexing, identifying, and disseminating lawyers’ prior work and collective expertise helps legal firms and departments solve legal and business problems more effectively. 

 

Enhanced onboarding and learning 

Legal-focused generative AI tools help users get up to speed quickly without extensive training, whether they are new to a firm or gaining knowledge about an unfamiliar area of law.  

These tools also help users learn new skills in a hands-on way as they work, reducing the need for as many formalised skill-development interventions, saving time and money. 

 

Those unfamiliar with a given area of law may struggle to know where to start or which language is most applicable in searching for resources.  

Generative AI tools that can be prompted using plain-language queries allow users to access faster answers to complicated legal questions and rapidly organise information and precedents that can help them develop successful arguments.   

 

Trustworthy security and privacy 

A professional legal AI tool licensed to a particular institution or firm provides a far more secure work ecosystem than a public-facing tool with few or no data controls. While legal professionals must always use caution regarding what data they use with AI tools, they can input a range of proprietary data with far less risk in a tool that has been designed specifically for legal professionals.  

Additionally, since legal-specific generative AI tools are trained on high-quality legal content, law firms, and in-house legal departments can be confident that their output will be more trustworthy and accurate than other large language models. 

 


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