Legal’s Modern Data Problem: Why AI Is Now Essential Infrastructure

Across the business spectrum, the modern work environment is rapidly becoming multi-app and hyper reliant on communication tools and project management platforms that have become critical to maintaining organizational productivity. Many workers today say they now have to switch between multiple platforms hundreds of times in a single workday, which is pointing to a broader transformation that continues to upend every aspect of the working world.

The legal industry, once perceived as a slow mover on technology adoption, is now witnessing its own period of accelerated innovation and transformational change. This is in part due to the rise of sophisticated and battle-tested AI tools that are beginning to redefine the profession and the way attorneys practice law.

This shift towards workers using more apps is leading to an exponential increase in user data, and in the legal world it is starting to have an impact on fact investigation, legal analysis and case litigation. The volume and nature of digital evidence in litigation is changing dramatically, and the process no longer revolves around email threads and PDF attachments. Evidence extends beyond the document format and is becoming more dynamic in nature. Slack threads, text exchanges, Google Doc comments, screen recordings, meeting transcriptions, emojis, partial messages, and auto-saving cloud content – just to name a few– define modern evidence. This paradigm shift means more legal pros are investing in AI to manage emerging data types that are making cases longer and more complex.

These formats are generated across dozens of apps, occurring at different times across time zones, disappearing or updating automatically, which causes shifts in meaning based on timing, reactions, and edits. Recently,  Microsoft’s Work Trend Index showed that the average worker is sending more digital messages than ever. Even with shorter communications from messaging tools, important information can easily be distributed across micro-interactions.

The legal sector may be foreshadowing what the entire enterprise world is experiencing: a massive, irreversible shift toward unstructured, multimodal data. Getting a handle on all this data means that leveraging AI is no longer optional; it’s becoming the only scalable way to manage, interpret, and act on the deluge of information.

The New Digital Evidence Landscape

Lawyers today have come to rely on technology-driven solutions like e-discovery, which is the aspect of identifying, collecting and producing electronically stored data. In the legal industry, legacy e-discovery tools were built during a time when email dominated corporate communication and documents were static, single-version files. They assumed that one file is one stable artifact, attachments are stored locally, and metadata is consistent and reliable.

The current reality looks nothing like that. As legal teams take on more complex litigation and high-stakes matters, communication today now happens much differently. Now, we get fragments of conversations and data points dispersed across Slack channels and DMs, Microsoft Teams chats that blend meetings, chat logs, and file comments, and collaborative platforms like Google Drive and Microsoft 365 that store version histories and in-app chat and comment features.

One of the reasons legal is undergoing such a massive transition is that legacy tools weren’t designed for hyperlinked documents that evolve over time, version histories that break the “single source of truth” concept, or communications scattered across dozens of apps. Reconstructing “what actually happened” is nearly impossible without the help of modern technologies.

Consider a typical workplace conversation. It begins with a Slack brainstorm, moves to texts, escalates in a Zoom call, shifts to comments inside a shared Google Doc, and ends with a recap email. No human- or legacy-software can reliably rebuild this narrative at scale. Lawyers must trace timelines that span multiple platforms, include dozens of file types, span conflicting time zones, have incomplete metadata, and may be missing or have overwritten edits. A recent DISCO study shows how collaboration tools like Slack and Teams have become key drivers in making the litigation process longer and more complex.

In the legal world, complex data types represent new behaviors, and modern communication tools have distinct emotional and contextual cues. Consider sarcastically-toned emojis or GIFs and memes that convey reactions without text. Interpretation now requires understanding relationships between messages, not just reading static content.

The Legal Tech Investment Landscape is Booming

VC interest in legal technology has been mounting ever since the launch of ChatGPT and the generative AI boom in early 2023. Much of this is driven by the shifting demands for law firms and corporate legal departments, who are looking for advanced tools that can drive efficiency, speed, accuracy, defensibility, cost predictability and keep up with exponential growth in data sources. AI and GenAI-assisted legal tools are now becoming essential infrastructure in litigation.

GenAI tools are starting to prove how they can assist legal teams in ways that are often beyond human capabilities. This includes helping lawyers automatically group related messages and documents, reconstruct timelines across platforms, identify communication patterns and sentiment, and summarize vast collections of data that can surface only the most essential facts.

The NIST AI Risk Management Framework formalizes this partnership model: AI + human-in-the-loop is the gold standard for high-risk environments. AI amplifies human judgment; it doesn’t replace it, and can handle volume, pattern detection, clustering, summaries, and organization. But at the end of the day, lawyers still handle interpretation, ethical judgment, legal strategy, narrative development, and decision making.

How AI Improves the Litigation Lifecycle End-to-End

The review process is drastically evolving, as attorneys are now using AI to tap into the mountain of evidence and reduce the amount of datasets that attorneys must touch directly. Modern data processing, supported with AI advancements can help lawyers synthesize large volumes of data in novel ways by surfacing trends and duplication.

AI amplifies the lawyer’s ability to seek clarity and find context to build the narrative of their case– reconstructing who participated, what they said, when events happened across the different sources of evidence. It can dramatically accelerate speed-to-evidence and surface insights humans often miss, as well as detect sudden communication spikes, behavioral anomalies, new participants joining sensitive conversations and recurring topics across channels.

Human oversight improves, it doesn’t disappear. With the implementation of AI in workflows, lawyers focus on validating results, investigating anomalies, interpreting meaning and building strategy. AI handles the heavy lifting, but humans will always handle the reasoning.

How Does Legal Adapt to an AI-Driven Future?

Legal teams face the same unstructured data challenges as every other sector, and the industry is simply dealing with the consequences sooner and under higher scrutiny. Litigation requires defensibility that sets a benchmark for all industries. AI outputs in legal must be explainable, traceable, auditable, and ultimately defensible in court. If AI can operate in this environment, it can operate anywhere.

AI shifts from a point solution to core operational infrastructure, and legal teams will move from experiments to integrated workflows with formal governance.

What’s Next: Preparing for an AI-Centric Legal Workflow

Across the enterprise landscape adoption timelines are shrinking. A recent PwC study indicated that a third of CEOs say GenAI has increased revenue and profitability over the past year, and half expect their investments in the technology to increase profits in the year ahead.

In the legal sector, data shows that over a third of legal professionals have already integrated generative AI tools, with many expected to do so within the next year.

AI will take over more first-pass document review. Human reviewers are shifting from reading everything to validating AI output. According to a 2025 Thomson Reuters report, the primary application of generative AI among legal professionals and in-house departments is document review (74% of users). Lawyers will need new skills around AI literacy, validating and supervising tools, understanding errors and limitations, and effectively integrating AI into workflows.

Conclusion

As the legal profession continues to navigate a rapidly changing environment, attorneys will be faced with the same data explosion confronting all industries but under heavier scrutiny, with higher stakes, and tighter timelines. As communication spreads across dozens of platforms, AI becomes the only scalable way to understand modern evidence.

Legal teams adopting AI aren’t chasing hype; they’re building a blueprint for how every enterprise will handle multimodal, unstructured data. What’s happening in litigation today is a preview of the future for everyone.