Law firms are testing a new approach to data management as they race to adopt artificial intelligence tools, according to legal technology leaders who spoke on a panel session Tuesday in New Jersey.
The discussion centered on how firms can organize their data more effectively to support AI applications, which depend on clean, structured information to produce reliable results. Panelists said many firms are discovering that their existing data systems were never designed for the kind of machine-readable formats that AI tools require.
"Firms are realizing they can't just bolt AI onto their existing infrastructure and expect it to work," one panelist said. "The underlying data has to be organized differently, or the AI will simply amplify the problems that were already there."
The data problem at the heart of legal AI
Law firms have accumulated decades of documents, emails, billing records, and case files stored across disparate systems. Much of that information sits in formats that AI models struggle to parse, such as scanned PDFs, legacy word processing files, and inconsistently labeled folders.
The panelists said firms that want to use AI for tasks like document review, contract analysis, or legal research need to first invest in data cleanup and standardization. That work involves tagging documents with metadata, converting files to machine-readable formats, and establishing consistent naming conventions across practice areas.
Some firms are creating dedicated data governance roles, while others are turning to outside vendors that specialize in legal data management. The panelists cautioned that there is no one-size-fits-all solution, and that firms need to assess their specific needs before committing to a particular approach.
Competitive pressure drives urgency
The push toward better data management comes as clients increasingly ask law firms about their AI capabilities. Corporate legal departments are under pressure to control costs, and many see AI as a way to reduce billable hours on routine tasks.
Firms that can demonstrate a working AI infrastructure may have an advantage in pitching for new business, the panelists said. Those that lag behind could find themselves at a competitive disadvantage as the technology becomes more widespread across the industry.
One panelist noted that the current moment resembles the early days of e-discovery, when firms that invested early in the technology gained a lasting edge over rivals that waited. AI adoption in legal work is following a similar pattern, they said, with early movers likely to shape how the technology is used in the profession.
The practical path forward
The panelists offered several recommendations for firms beginning this work. Start with a pilot project in one practice area rather than attempting a firmwide overhaul, they said. Measure the results carefully, and use those findings to build a business case for broader investment.
They also urged firms to involve lawyers in the process, not just IT staff. Attorneys know which documents matter most and how they should be categorized, making their input essential to building a data system that actually supports legal work.
Training is another piece of the puzzle. Even the best data management system will not help if lawyers do not understand how to use AI tools effectively or what their limitations are.
Why this matters for legal professionals
For lawyers and legal support staff, this shift means the way they organize and handle documents is likely to change. Firms that adopt structured data practices will expect attorneys to tag files consistently, maintain accurate metadata, and follow new procedures for how information is stored and labeled.
Legal professionals who understand how data quality affects AI output will be better positioned to work with these tools and to spot errors when they occur. That knowledge is becoming a practical skill, not just an IT concern, and it may factor into how firms evaluate and promote their lawyers in the coming years.
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