When you hire a law firm, you buy knowledge. Knowledge of the law, of course, but also knowledge of the market: what the other side conceded in the last hundred deals like yours, which clause actually gets litigated, and which “standard” term is not quite standard. More than any individual document, that accumulated experience is the product.
This raises an increasingly important question as the legal industry incorporates AI: where does the firm keep that knowledge?
At Most Firms, the Filing System Is a Person
Amazingly, most knowledge at traditional law firms is stored solely within people’s minds. The partner who has seen two hundred financings understands the market. The associate who negotiated last year’s version of your vendor agreement remembers the fallback positions that worked, and the paralegal has always silently and heroically kept the whole operation going. Precedent is encoded in inboxes, in desktop folders, and in documents named “FINAL_FINAL_REALLY_FINAL_v7," meaning that the firm’s most valuable assets leave the office every evening, and can walk away from the firm at any time.
That structural risk is only worsening. Recent industry reports put associate attrition at around 20 percent a year, with some studies placing firm-wide turnover across all seniority levels closer to 27 percent. The National Association for Law Placement estimates that replacing an associate costs one and a half to two times their salary. Pricing the lost organizational knowledge due to personnel churn is even more difficult. Thomson Reuters has written about firms scrambling to preserve institutional knowledge as senior lawyers retire, because the strategies that worked and the mistakes learned along the way can only be transmitted to the next generation if they are systematically recorded.
The instability of institutional knowledge costs clients. Under hourly billing, the inefficiency of relearning is charged to clients who pay for the rebuild of expertise as new lawyers re-learn your business, your documents, and your preferences. Thus, in a way, the traditional model incentivizes knowledge loss, since filling gaps puts money back into the firm’s pocket.
Writing It Down Is Easy
These observations aren’t novel. Law firms have maintained precedent banks and knowledge-management departments for decades. In practice, however, these efforts run into several hurdles.
The first is the incentive structure created by hourly billing. When revenue is measured in hours, time spent making the next matter faster is time not billed. Capturing knowledge thus never becomes more than a side project.
The second issue, affecting even in-house teams, is difficulty in getting approval for “strategic investment in systems that would deliver efficiency gains in the medium and long terms” as opposed to simply hiring more attorneys.
The last issue is staleness. A repository of forms and positioning on common issues that nobody updates quickly becomes outdated in fast-moving practice areas.
At General Legal, we build with the idea that a knowledge base is valuable only if it is used on every matter and improved by every matter.
Knowledge at General Legal
General Legal, as an AI-native law firm, is set up at its core so that the firm’s knowledge lives in both systems and people. General Legal’s proprietary AI platform is trained on an extensive body of commercial-law knowledge, backed by our attorneys’ years of expertise. Our platform then brings that guidance to bear on the next matter, for every client, from day one. We even maintain bespoke playbooks for individual clients, so the system knows your terms, your redlines, and your preferences as it approaches every new matter. This means that the hundredth contract review is informed by the ninety-nine that came before it. By incorporating knowledge management directly into our attorneys’ processes, we continuously expand its value.
We run the rest of the firm the same way. Policies, processes, and project status are housed in structured workspaces rather than in individual attorneys’ inboxes, that way they're readable by attorneys and tools alike. Software engineers call this managing the “bus factor”: the number of people a project could lose before it grinds to a halt. We run the firm so that no single person’s absence puts a matter, or a client relationship, at risk.
The Human Part
However good the playbook, it only records judgment, still requiring judges for effective use. Our model pairs AI that is continually training on the law with experienced attorneys who do what a model cannot, for instance, validating the corner cases, making judgment calls that depend on clients' wishes, and, just as importantly, identifying the model's weak points. New and emerging areas of law, from AI governance to evolving privacy regimes, don’t come with a hundred precedents, so attorneys lead and the system learns behind them. As articulated in an earlier post: the AI tells you what is wrong; the attorney decides what to do about it. The playbook updates in accordance with the attorneys' decisions, providing important context for similar cases in the future.
What This Means for You
For clients, knowledge housed in systems manifests in three ways.
- Consistency: Your third matter is handled with everything the firm learned on your first two, regardless of who staffs it.
- Speed: Faster turnarounds are achieved because less time is spent re-deriving known answers.
- Predictability: Work informed by an ever-deepening playbook is work we can scope, which is part of how we offer flat, published pricing in the first place. Your lawyer’s memory is valuable, but your legal history exists systematically.
Working With Us
If you’re a founder or an operator who would rather build on your firm’s accumulated knowledge than pay to rebuild it, General Legal offers flat-fee, fast-turnaround counsel backed by experienced attorneys. Ready to see the difference an AI-native approach makes? Sign up here to get started.
Sources
• “How to save law firm institutional knowledge,” ThomsonReuters
• “How law firms move from human to institutional knowledge,” Thomson Reuters
• “The Problem of Attrition,” Lawyers Mutual
• “Balancing Attorney and Machine at an AI-Native Law Firm,” General Legal