Using AI in Case Management: The Perfect Early Use Case for Your Law Firm

While the hype around artificial intelligence (AI) for legal has been present for years, many law firms and litigation departments are still in the early stages of assessing, adopting, and implementing AI solutions. As legal teams explore ways to incorporate AI, approaches and results vary. However, early indications from industry leaders and research suggest that a use-case-focused approach, rather than broad AI implementations, offers the best return in terms of adoption and results. This strategy, which prioritizes integrating AI into existing workflows, delivers value by addressing specific challenges for a partner or practice area. 

While many law firms currently use AI for legal research, eDiscovery coding, and billing narrative drafting, case management may be the most promising and valuable use case yet. From pre-litigation to trial preparation, case management encompasses the critical processes that happen throughout the case lifecycle, including initial case assessment, hot and relevant document analysis, case strategy, chronology creation, deposition preparation, transcript management, and more. 

Adding AI to case management processes is an excellent starting point where teams can realize value immediately, prove their AI strategy, and quickly gain a competitive advantage both in court and in winning future cases. Because case management uses a predefined document set that has already been filtered for relevance and importance to the case during discovery, it reduces the chance of AI returning irrelevant information, helping to win over reluctant users, establish credibility, and ensure that attorneys remain in control. When compared to other AI use cases like eDiscovery, the smaller data sets used in case management also means that applying AI to case management has a much higher return on investment for law firms. 

Incorporating AI into case management workflows offers clear benefits. Here’s how

Using a case-focused solution instead of broad tools 

There are two main approaches to AI. The first approach involves adopting a broad, standalone AI tool that can be used for anything but may require extensive customization or prompt engineering. The second approach prioritizes practical applications, leveraging AI designed for specific use cases. For many law firms still in the early stages of AI adoption, focusing on use cases is the best starting point. 

As an illustration, consider using AI in this case management workflow example: 

• Reviewing content within hot documents  

• Highlighting, extracting, and collaborating on the information 

• Connecting related data together like events, characters, and issues 

• Structuring this data to be actioned 

• Drafting, reviewing, and creating the final work product  

If you apply a standalone or broadly focused AI tool to perform labor intensive, but important, tasks like data and text summarization, extraction, and generation, the process can be less intuitive than you may expect from systems designed to save time.  

Most legal AI tools use large language models (LLMs) that must train themselves using a source set of documents and require users to understand how to create the right prompts to get meaningful results. While this approach to AI ensures that outputs are based on relevant information, it also requires you to move documents out of one system into another — a manual process that adds another potentially frustrating step to already complex workflows. When you pair this barrier with a lack of transparency about how AI reaches conclusions and lawyers’ concerns about the accuracy of AI, it’s a recipe for distrust, frustratingly low adoption rates, and limited ROI. 

On the other hand, taking a use-case focused approach by adopting a legal case management solution with integrated AI elevates existing workflows instead of interrupting them. It also provides clear guidance for using AI, adding context, trust, and control.  

Let’s take building a case chronology as an example. Instead of asking a standalone AI tool to identify all the events from 20,000 case documents by importing them to the system and then exporting the results, a case management platform with integrated AI will already contain that data, enabling the AI to deliver answers that are immediately actionable without any additional steps. In addition, lawyers will be more inclined to trust integrated AI that can cite sources and link directly to underlying evidence when it suggests an event to add to the chronology. While AI surfaces insights, lawyers ultimately determine how that information is used – giving them final say on what gets added. 

By enhancing the chronology building segment of the litigation lifecycle, AI can deliver measurable efficiency contributing toward the overall ROI of the implementation. Now think about what AI can do when integrated into other aspects of trial preparation. 

Using AI to address litigation trends 

Beyond enhancing workflows, case management is an obvious use case for AI as data volumes and caseloads grow. This summer, Ari Kaplan Advisors released a report based on interviews with litigation support directors exploring market trends, challenges, and technology. The research revealed:  

• 93% reported that the volume of data in an average litigation case is increasing. 

• 60% believe that the continued growth of case data volumes presents challenges. 

• 83% expect caseloads to rise in the next 12 to 18 months. 

As data volumes and the litigation caseloads increase, the manual work of reviewing documents, extracting information, highlighting patterns, and creating narratives becomes more expensive, time consuming, and inefficient. Incorporating AI offers litigation teams a way to scale despite these compounding challenges. 

When considering using AI in litigation processes, 87% of respondents indicated that AI-assisted case management software is a competitive advantage. Further, when considering how AI will transform case management, the top uses were: 

• 100% document analysis  

• 90% transcript management 

• 87% chronology creation 

• 77% case strategy 

 Several respondents already use AI-enabled case management platforms. “This technology streamlines the case management process because it helps you automate your workflow and save time to focus on more strategic parts of your case that require critical thinking,” one respondent said. 

Advantages of using AI for case management  

 Beyond providing a targeted focus for AI integration and the ability to scale workflows as caseloads increase, case management is a good entry point for AI for other reasons.  

When using AI, quality input equals quality output. Unlike eDiscovery where AI must comb through irrelevant and duplicative information, case management projects have already filtered through documents to get to the core of what’s important. While AI can be used to identify discoverable documents, using AI on only relevant case information delivers higher-value outputs.  

Additionally, selecting tools that provide guidance, citations, and control will help secure adoption. For example, Opus 2’s AI-enabled legal case management solution only leverages selected data, preventing errors and erroneous results from having a negative impact on a case or wasting litigators’ time. Most importantly, lawyers remain in control of the process — contributing their valuable knowledge and experience to shape outputs. 

Finally, success in litigation and case management can serve as a successful pilot to prove value and alleviate concerns from reluctant users. By specifying the functions you’re trying to improve with AI, then collecting performance KPIs, litigation teams can demonstrate they’ve achieved measurable progress toward their goals. More importantly, the team can share personal anecdotes of how AI-enhanced case management helps their day-to-day work, winning over new users. 

Give your litigation team every advantage 

Given the changing market conditions, growing competition, and clear benefits of integrating AI into case management workflows, litigation teams with outdated, legacy applications may quickly find themselves losing their edge. To meet these challenges and gain a competitive advantage, now is the time for law firms to upgrade to AI-assisted, best-in-class case management.

Beau Wysong is Senior Vice President of Global Marketing at Opus 2, a leading legal software and services provider.