In the first part we looked at risks, and the second covered how in-house legal teams can establish governance. In this third part, we look at specifically how in-house legal can use generative AI to support their work.
ChatGPT and generative AI is a transformative technology that is going to impact the way we work, including the potential for in-house legal teams to develop innovative new approaches and internal services. But it also comes with considerable levels of risk, and in-house legal teams have an important role in guiding organisations to minimise their risk exposure in using ChatGPT.
One focus for the continuing media attention on generative AI has been what the impact will be on people’s jobs and roles. This has included speculation on which professions and sectors will be impacted the most with a common sentiment being that the legal sector has the potential to be one of the most affected.
Within the legal sector, the positive and negative impact of the automation of more routine tasks has been a topic for discussion for a while, and to a certain extent the impact of generative AI and ChatGPT can be regarded as the latest evolution of that debate.
Perhaps what’s different from previous discussions, is the speed and depth with which generative AI could support and change some areas of legal work, principally around making teams more productive and speeding up or even eliminating more routine tasks. Some of the potential to help in-house legal teams to be more efficient and to innovate are both intriguing and exciting, although there are some use cases where AI is already making inroads.
However, as we know there are significant risks with generative AI which clearly limit how in-house legal teams can use AI, particularly a public service like ChatGPT. There is the well-publicised case of the US law team who used generative AI for research and referenced non-existent legal cases that AI had simply made up, where the team clearly fell for ChatGPT’s ability to “hallucinate” and present answers confidently, not only making up the cases, but then also confirming that they could be found on legal reference databases.
How will generative AI be used by in-house legal teams?
In considering how in-house legal teams will be using generative AI, it is worth considering the basics of what a generative AI service like ChatGPT does. It’s not just about generating text, it can also:
- Generate images.
- Summarise text.
- Translate text.
- Identify subject labels and tags or classify items based on existing keywords.
- Research topics (albeit with the potential for errors).
- Understand questions and prompts made in natural language.
- Give answers in natural language.
- Extract or change relevant parts of a document.
- Produce code.
- Look through large amounts of content and data extremely quickly.
- And more!
By using and combining these capabilities, generative AI has the potential to carry out some sophisticated processes that can support in-house legal teams in their work.
For example, in-house legal teams mainly work with text, so generative AI can support productivity by being worked into routines where in-house teams are producing written responses in their daily work. This could involve summarising the points of a meeting, simplifying existing text, correcting punctuation, helping create an email or producing an overview of the impact of a particular piece of legislation, for example. Here generative AI is more playing the part of an assistant, speeding up the creation of text rather than being relied upon to produce the text itself, saving time by automating repetitive or simple tasks.
The legal use cases for generative AI
Above and beyond using generative AI to automate repetitive everyday tasks, there are a number of use cases for in-house legal teams where generative AI could be applied to make a real difference, although many of these would need a dedicated solution or product.
Deloitte Legal highlight a number of different use cases where generative AI could be used for:
- Litigation: Analysis of case data for rapid early case assessment, minimising the risk of protracted legal action.
- Commercial contracting: Identifying the most likely outcome relating to particular clauses in contracts.
- M&A: Using generative AI to speed up due diligence where there are large amounts of data to analyse.
- Competition / anti-trust: Generating an anti-trust risk assessment in large mergers involving multiple jurisdictions.
- Regulatory compliance: Conducting a gap analysis across two or more area of regulation.
- Knowledge management: Generating updates and training materials for the business.
- Legal operations: Automated RFP response scoring across response documents.
Again, there will be additional use cases where generative AI is being used to analyse and digest large volumes of content and producing valuable output, ultimately speeding up processes that were previously very time-consuming and resource intensive.
The impact on legal technology and products
All the above use cases mentioned by Deloitte Legal may have dedicated products that will help support them and which incorporate generative AI. In fact, in-house legal teams may first get their real taste of the power of generative AI through the targeted products that serve the sector. Legal tech and information vendors are working on integrating generative AI to improve existing products, with Thomson Reuters having even created their own proprietary Large Language Model.
There’s an interesting article from the FT that lists the numerous tools incorporating generative AI that are being worked on or improved to speed up legal work.
The team at iManage are working on integrating a conversational search tool into their product, while LexisNexis are doing something similar. A new “AI legal assistant” called Leah analyses contracts and helps you create new documents, and is part of a growing ecosystem of legal contract solutions that are powered by AI.
PwC Legal Business Solutions are working on a legal knowledge subscription service that incorporates AI, and also implementing Leah with clients. And this is just the tip of the iceberg; we can expect to see more products that incorporate generative AI specifically targeted to increase the productivity of in-house legal.
Generative AI and knowledge management
Generative AI also has great potential in the area of knowledge management, traditionally an area of interest for in-house legal teams and the legal sector in general.
For example, the ability to search for internally generated documents and precedents is often a painful experience, with items consistently hard to find. Improving enterprise search is a notoriously difficult and expensive exercise and can involve integrating a new search solution, implementing an enterprise taxonomy and then tweaking the solution to improve results.
Generative AI has the potential to transform the search experience, including:
- automatically generating tags and metadata for documents that will make them more findable,
- generating document summaries to help users know if they have found the right item,
- extracting answers from documents to specific questions so search results are returned with even more context,
- allowing for richer search queries in natural language,
- searching through vast amounts of unstructured data and content at lightning speed.
Another area of knowledge management where generative AI could have a major impact is the field of model documents – and in particular building contracts and agreements. Generative AI can both review documents to suggest improvements or extract particular data, but then it could also build sophisticated documents based on different criteria such as employee contracts, NDAs or leases.
AI is already supporting in these areas via solutions like Microsoft’s SharePoint Premium (formerly SharePoint Syntex) but generative AI looks set to advance what is possible. There are also many AI-driven products that are focusing in on the area of contracts.
Conclusion
Generative AI has exciting opportunities to support the work of in-house legal and teams embracing these now will be given a head start. But this is a very fast-moving area and there will be further changes ahead. In the final part of this Viewpoint series I’m going to look into how some of the products and players in the generative AI space are evolving and how this might impact the work of in-house legal teams.
