Document processing
17 min read
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Oct 30, 2025
Discover how AI is creating opportunities beyond traditional case management, enabling predictive insights, automated workflows, and intelligent decision support.
Imogen Jones
Content Writer
You’re staring at your overflowing inbox.
Your case files live across three systems, your notes are trapped in PDFs, and the latest client update is buried somewhere in an email chain titled “Re: Re: Urgent – Updated draft 2.”
The software that was supposed to make life easier, your case management system, mostly reminds you of what’s overdue. It keeps you organized, but not ahead.
According to LexisNexis, 95% of legal professionals believe AI will have a notable impact on law, and 61% are already using it. One of its most immediate applications is in case management, the operational heart of most legal practices.
Traditional legal case management software has helped structure and digitize workflows, but it often falls short in providing proactive, intelligent support. AI case management software moves beyond basic case tracking to offer predictive insights, automated workflows, and intelligent decision support.
This guide examines AI for case management, outlining the key platforms, implementation strategies, and ethical considerations shaping this new era of legal technology.
In this article:
Understanding AI case management
Leading AI case management platforms
Implementation strategy and practice integration
The future of AI case management
Understanding Case Management in 2025
Case management is the structured process by which law firms and legal departments organize, track, and advance their matters from intake to resolution. It involves coordinating documents, deadlines, communications, and tasks across multiple stakeholders, and ensuring that every action taken in a case is timely, accurate, and properly recorded.
Of course, the demands vary by domain. For example, a civil litigator must track every filing deadline and evidentiary document with precision, while a corporate lawyer juggles contracts, approvals, and compliance workflows.
From Traditional Case Management to AI Legal Practice
We began this article with you staring at an overflowing inbox, a maze of digital files, and a slightly outdated case management system. As frustrating as that sounds, it already represents enormous technological progress.
Decades ago, case management was entirely paper-based. Every matter lived in a manila folder stuffed with handwritten notes, typed correspondence, and filings. Updates were passed around by memo or phone call, and the physical file itself was the single source of truth.
The first glimmers of digitization appeared in the 1970s and 1980s. Legal research began to move online through LexisNexis (1973) and Westlaw (1975). IBM’s Displaywriter, and later Microsoft Word for DOS, replaced typewriters.
Firms began keeping client databases and billing records on local machines, often using programs like Lotus 1-2-3 or dBase. The first dedicated case management software is often considered to be SolCase by Solicitec, launched in 1985. It offered centralized client records, automated reminders, and searchable digital files.
By the 2000s, a second wave of modernization was underway. Cloud-based practice management software replaced on-premise servers, digitizing workflows, automating key tasks, and making case information securely accessible from anywhere.
But those systems still had limitations. A traditional platform can store deadlines, for instance, but it can't interpret a pattern in case outcomes or draft a summary of the latest hearing that flows seamlessly into later workflows.
That’s the gap AI is beginning to close.
This shift is arriving at a moment when lawyers are under growing pressure to do more with less. Studies show that roughly 67% of a lawyer’s day is spent on non-billable tasks like administration, making it clear that traditional tools weren’t fully solving the productivity puzzle.
That caution around generative AI is increasingly giving way to curiosity and adoption, with conversations shifting from “Can AI be trusted?” to “Which AI should we use?”
Established case management systems are beginning to integrate AI capabilities, adding intelligent assistance to tools that firms have used for years. Even more excitingly, a new generation of AI-native tools is emerging, suitable for professional-grade case management. These systems combine the reasoning power of generative AI with safeguards around accuracy, transparency, and data control.
By layering artificial intelligence onto case workflows, routine tasks can be intelligently automated and case data becomes a source of actionable intelligence. We explore exactly what this looks like below.
Core AI Capabilities in Modern Legal Case Management
Modern AI case management platforms bring a toolkit of powerful technologies to streamline legal workflows. Here are the core AI capabilities transforming how lawyers manage cases.
Case management lives and breathes through documents, such as pleadings, correspondence, discovery materials, contracts, and filings. Every case depends on how effectively these materials are reviewed, organized, and connected.
AI document analysis can rapidly read and interpret contracts, pleadings, discovery materials, and more. For instance, an AI system can extract key details from a contract (parties, dates, obligations) or flag critical terms in a stack of leases without a lawyer reading each one.
The immediate advantage is efficiency: tasks that once took days can be completed in minutes. But the deeper impact lies in quality and consistency. AI systems can detect subtle relationships across documents (a recurring clause, a timeline discrepancy, a missing exhibit) and turn isolated files into a coherent case narrative.
Learn more about AI for contract and document analysis.
Once information is digitized and organized, the next step is to automate how it moves through the case. Traditional software helps track tasks and deadlines; AI extends that capability by learning from context and adapting to change.
For instance, an AI system can ingest a court scheduling order and automatically calculate all related deadlines, populate calendars, and alert team members. It can also automate intake forms, document generation, and routine client updates, freeing up lawyers and support staff to focus on analysis and advocacy rather than administration.
As firms accumulate digital case data (outcomes, timelines, win/loss rates, billing trends), AI can turn that information into predictive intelligence. This emerging field, sometimes referred to as jurimetrics, applies data science to legal decision-making.
By analyzing historical data, predictive models can estimate the likely duration or outcome of a matter, forecast litigation costs, or suggest optimal settlement ranges. For example, based on variables such as jurisdiction, opposing counsel, and claim type, an AI might estimate an 80% chance that a personal injury case will settle under $100K rather than proceed to trial.
These insights enable lawyers to give clients evidence-based recommendations and to manage risk with greater precision.
A law practice lives or dies by its client relationships, and AI is helping firms communicate more clearly and consistently. Intelligent assistants can answer routine questions, send updates when key milestones are reached, and personalize messages based on case details.
The result is faster, more transparent communication, and fewer missed updates or administrative delays. By handling predictable exchanges, AI gives lawyers more time to focus on the conversations that truly matter.
One of the most promising developments for case management is the rise of AI agents, systems capable of handling complex, context-aware tasks within legal workflows.
Unlike traditional workflow automation, which executes fixed rules, AI agents combine reasoning, language understanding, and real-time data access to act dynamically within a defined scope of responsibility. In a case management setting, an AI agent might review incoming discovery files, extract and classify relevant documents, summarize findings for an attorney, identify and intelligently prioritize due dates, and even cross-reference new information against prior filings or case notes.
It can do all these things by working through steps logically, referring to internal knowledge and using tools, assisting in case management much in the same way a paralegal or junior lawyer might.
You can browse an extensive list of V7's AI agents here: AI Agent Library.
Don't spot the perfect fit for your case management workflow? Get in touch with our expert team for a bespoke demonstration.
AI Case Management Platforms
Legal tech is in a state of flux as established software providers add AI features and new AI-native platforms emerge. In this section, we overview some of the leading platforms that integrate AI with case management, from all-in-one practice management suites to specialized AI assistants.
Enterprise Legal Practice Management with AI Features
Large and small law firms alike are often already using practice management software to handle cases, contacts, billing, and calendaring. Providers of these platforms have begun adding AI capabilities to enhance their systems.
Widely regarded as a market leader in cloud legal practice management, Clio manages everything from cases and documents to billing and client communications.
In late 2024, Clio introduced Clio Duo, a generative AI assistant built directly into its platform. Users can quickly retrieve client and matter details via natural language queries, without manually searching through records. Clio Duo also provides one-click summarization of any text document in the system, generating a summary that can be saved as a new file for reference.
Another major cloud practice management suite, MyCase caters to firms’ needs from document management to time tracking, and it too has embraced AI. In October 2024, MyCase rolled out MyCase IQ, a set of generative AI features within its platform.
Initially, this included document summarization and smart text editing tools that help lawyers digest documents quickly and refine content. MyCase has also recently introduced an AI conversational interface called “ChatIQ” that allows users to retrieve case information by asking questions in natural language.
Visualfiles is a long-established case and workflow management platform used widely by law firms and corporate legal teams in the UK. Lexis has begun integrating AI capabilities into Visualfiles to enhance document processing, case automation, and decision support.
An all-in-one practice management solution that is unique for including built-in legal accounting (general ledger, trust accounting) along with case management. CosmoLex’s key pitch is having everything in one system.
When it comes to AI, CosmoLex’s approach has been about automated workflows and template-driven processes. For example, CosmoLex introduced Automated Workflows that let firms create template task lists that trigger based on events.
Opus 2 is a leading platform for litigation and arbitration case management. In recent years, Opus 2 has expanded its platform with AI-enhanced features designed to accelerate case analysis and streamline preparation. These include tools for intelligent transcript review, automated document linking, and evidence summarization.
AI-Native Legal Platforms and Document Intelligence
While traditional platforms are adding AI, some solutions have been built from the ground up with AI at their core. These AI-native platforms often focus on specific advanced capabilities like deep document analysis, multi-document cross-referencing, or conversational interactions. They can work as your primary case management system or as an integrated component.
Let’s explore a few leaders in this category:
V7 Go is a flexible AI agent platform built for document-intensive industries such as law and finance. It brings intelligence and automation to every stage of case management.
Teams can build custom AI agents that automate entire case management workflows (or specific tasks within them) from intake and document review to task tracking and reporting. Agents can trigger reminders, generate summaries, and organize correspondence by matter, cutting down on manual updates and reducing the time lawyers spend searching for information.
The platform integrates seamlessly with existing case management tools, CRMs, and document repositories to create a unified and connected workflow.
Every agent within V7 Go operates with full traceability. Each extracted clause or summary includes a direct link to the source document and page, so lawyers can instantly verify the context before acting.
Harvey AI is an AI platform built specifically for the legal and professional-services sector. For case management, it offers a mix of automation, insight and workflow optimisation. It can ingest large collections of case-related documents, track deadlines and matter statuses, generate or summarise key materials, draft initial versions of filings, and flag relevant precedent or regulatory points.
Matterwise+ is a newer AI-native platform focused on end-to-end matter management. It integrates intake, document automation, and predictive task tracking into one intelligent workflow. Using embedded AI models, it can forecast deadlines, recommend next steps, and surface key case metrics in real time, making it suitable for firms looking to modernize without layering multiple tools.
Implementation Strategy and Practice Integration
Having surveyed the technology on offer, let’s turn to how you can choose the right solutions and implement them effectively in your firm. With so many options, it’s essential to align the tech with your specific practice and business needs.
Selecting AI Case Management Solutions for Different Practice Types
One size does not fit all when it comes to legal technology. A solo practitioner’s needs differ from a large firm’s, and a family law practice differs from a corporate litigation department. In this section, we provide a decision framework for choosing AI case management solutions based on firm size and practice type. Understanding your specific context will help identify which features and platforms are the best fit.
Solo Practitioners and Small Firms (1-10 Attorneys)
For solo practitioners and small law firms, effective case management often comes down to time and simplicity. You likely juggle client meetings, filings, and billing without the support of a large admin or IT team. The right AI case management platform should therefore be quick to deploy, intuitive to use, and affordable.
Small firms should focus on AI features that deliver immediate help in their everyday tasks. Key high-value capabilities might include: automated calendaring and reminders (so you never miss deadlines even without a full staff), document automation (like generating forms or standard pleadings automatically), and an AI legal research assistant for quick answers when you don’t have a law library team.
Mid-Size Firms (11-50 Attorneys)
Mid-sized firms need to manage higher case volumes across multiple practice areas while maintaining efficiency and collaboration.
At this size, firms often juggle different software for their billing, document management, CRM, and more. An ideal AI case management platform for mid-size firms should play nicely with these existing systems or consolidate them. Integration is key. For instance, if you already use Outlook for email and calendar, the case management tool should sync with it so attorneys don’t have to maintain two calendars.
Mid-size firms often have multiple practice groups (e.g., litigation, corporate, real estate, etc.). Choosing a platform with customizable workflows, templates, and permissions help ensure that each practice group benefits from AI and automation for case management without losing flexibility.
Large Firms and Corporate Legal Departments (50+ Attorneys)
Large law firms and corporate legal departments have unique needs that demand enterprise-grade solutions. Here, the scale of operations, complexity of matters, and higher stakes (financial and reputational) mean the AI case management system must be powerful, highly secure, and customizable.
Big firms often handle complex litigation, big transactions, or manage a huge volume of similar cases like high-volume litigation. They may also have internal workflows that are highly specialized. An out-of-the-box solution might not cut it; you likely need something that can be heavily configured.
The investment is larger, but so are the potential returns in efficiency and strategic insight. The mindset should be not just “how do we manage cases” but “how do we leverage all our firm’s knowledge and data with AI to deliver better outcomes and service.”
Implementation Best Practices for AI Case Management
Adopting AI case management software is not a simple flip of a switch. It requires thoughtful planning, testing, and training to ensure a smooth transition and real results. In this section, we’ll walk through key phases of implementation and provide best practices to maximize your chances of success.
Assessment and Planning Phase
Start by taking a hard look at your existing case management processes. Identify pain points, inefficiencies, and repetitive tasks. Where are lawyers and staff spending (or wasting) time? Perhaps you find that attorneys spend hours each week on manual data entry, or paralegals are burdened with combing through documents for key information. These are prime targets for AI automation.
As one framework, consider the metrics: only ~33% of lawyer time is billable, meaning 67% is consumed by non-billable tasks. Can AI reduce that non-billable portion?
Based on the workflow analysis, outline what return on investment you expect from AI. ROI can be time saved, cost saved, or quality improved. Try to set specific targets: for instance, “Reduce time spent on legal research by 50%” or “Automate 80% of client status update emails.”
Be measured, but ambitious. According to Thomson Reuters 53% of law firms are already seeing ROI from investing in AI. You can learn more about ROI for AI investments in our blog, How to Secure the Best ROI from Your AI Investment.
Pilot Program and Gradual Rollout
A common mistake firms make is trying to automate their most complex workflows first, or attempting a firm-wide rollout before proving value in a controlled setting. By starting small, you give your team time to develop confidence, competence, and compliant practices that will scale sustainably as both the technology and your expertise mature.
Choose workflows where:
The stakes are low enough that errors are manageable.
The volume is high enough to show clear ROI.
Success can be tracked through simple metrics like time saved or accuracy improvements.
Mistakes are easy to detect and correct.
Once a pilot is running, build feedback loops between the teams using the AI and firm leadership. Lawyers who work with these tools day-to-day will spot both the limitations and the hidden opportunities long before any executive dashboard does.
Training and Change Management
The human element is often the deciding factor in whether a new system thrives or withers. Lawyers and staff need to understand and trust the AI tools, and the firm needs to cultivate an environment that embraces innovation while maintaining client trust.
Plan comprehensive training sessions focusing on practical usage. It’s wise to go beyond one-off training; do an initial workshop, but also follow up with refresher sessions or Q&A drop-ins after attorneys have had a chance to use the system a bit.
You can find more information on change management and becoming an 'AI-ready lawyer' in our blog, How AI Will Affect Lawyers: A Practical Guide for 2025.
Ethical and Compliance Considerations in AI Case Management
Integrating AI into legal practice management brings tremendous potential benefits, but it also introduces new ethical and compliance challenges that law firms and attorneys must navigate.
The use of AI does not change the attorney’s fundamental obligations to clients, courts, and the public. In fact, lawyers have an evolving duty to understand technology’s capabilities and limitations.
Lawyers also have a duty under Model Rule 1.6 to keep client information confidential. When using AI tools, particularly cloud-based ones, you must ensure you’re not inadvertently exposing client data.
V7 complies with leading security and privacy standards, including GDPR and ISO 27001
Future Trends in AI Legal Case Management
We began this article with you staring at a packed inbox, case files scattered across digital platforms, deadlines closing in, and a case management system that feels more reactive than helpful. That doesn't need to be an accurate picture in a year's time.
AI is already here, and its ability to accelerate and enhance case management will only grow stronger over time. You'll see case updates, documents, and next steps surfaced intelligently and automatically. Notes will no longer sit buried in PDFs; the system will locate them, extract what matters, and link them to the right workflows. Emails will connect seamlessly to their corresponding matters, with key details summarized and ready for action.
Looking ahead, AI will move beyond organization into foresight. Systems will begin to offer outcome predictions, strategic recommendations, and risk assessments based on past cases. Client service will evolve too, with AI-powered portals giving clients real-time, personalized access to case updates. Even integration with court systems could one day automate filings and procedural notifications entirely.
For law firms, embracing AI case management is becoming essential for maintaining a competitive practice and delivering excellent client service. To enhance your legal practice and case management with V7 Go, book a demonstration.
