Last year, Law Firm 2.0, or the reimagined law firm, was a big topic at the TLTF Summit. Now, even AI-native law firms are part of the vernacular, designed from scratch around AI technology. Venture capital is flowing into firms built from the ground up, and existing firms strive to embrace AI more every day.
But what about the client? After all, they pay the bills and have access to the same technology. Perhaps the more consequential transformation is in the law department.
Just as existing law firms cannot discard their operations to start over, a law department has the same challenge. The idea of a reimagined Law Department 2.0 is real. Better, faster, cheaper is ingrained in corporate culture. Legal operations functions are more common and have led transformation for years, often at a faster pace than their Biglaw counterparts.
Corporate clients are upstream in the value chain, and the changes they make will prompt the law firm market to adapt. Generative AI was an accelerant, and new capabilities like agentic AI, legal open-source applications, and open-weight models are the equivalent of pouring gasoline on that fire.
This is the beginning of Law Department 2.0.
More Fundamental Questions, Bigger Changes
Here are three examples of big questions and changes being tested by different law departments.
Do we need that commercial software?
One progressive law department found itself building its own e-billing software as a potential replacement for vendor solutions. Whether they deploy it remains to be seen. The point is legal software categories will be challenged. Vendors need to double down to deliver value.
Why can’t we have a captive in-house law firm?
AT&T is building an in-house law firm. They are challenging the assumption that a law firm must be a separate and independent organization. Perhaps some matters can be captive to the corporation.
Do we really need to outsource litigation?
Historically, litigation isn’t an in-house function. But Google has decided to handle some disputes in-house. They are taking the lead on many patent and privacy matters internally. Google is challenging the assumption that litigation must be outsourced automatically.
Law departments have more opportunity to act on big ideas. Their actions will ripple across the industry. We will explore the ripple effects next month. In the meantime, here are four practical tips for empowered legal operations functions to build on.
Don’t Automate Bad Processes
The expression “paving the cowpath” comes from the idea that wandering cattle actually defined trails that became roads. The herd wandered for reasons, like grazing in a pasture that no longer exists. Roads need to be designed for human destinations.
Legal ops should begin by questioning processes. Why does it exist? Are there steps in a workflow that are no longer necessary?
For example, a process for entity compliance might currently task individuals across the enterprise to provide corporate registrations, insurance certificates, and permits. A better process might have AI agents access the information directly, without any human involvement.
Empower The Business
When processes are questioned, work may surface that is more effectively handled by staff within the business. Self-service automation guided by playbooks and defined approval processes can empower the law department’s customers. The standardization of preferred language, including fallback positions, may help a competent sales director close business faster, while engaging counsel only for exceptions.
Put Work In Its Proper Place
AI will create opportunities to empower business units and to move more work in-house or automate it out of existence. But not all work should be completed in-house.
Repeatable, high-volume tasks that align with the organization’s competencies and mission make sense to complete internally, especially when the work relies on company information.
But work that is a distraction or that is outside the core skills of the law department naturally belongs with outside counsel.
This is why the default is to engage a law firm for litigation. Disputes are distractions and can also grind against the gears of a well-run operation.
Patent prosecution makes sense to be outsourced if the work is infrequent. But if intellectual property is essential to the business, it may make sense to manage at least part of patent prosecution in-house.
It’s worth noting that even repeatable, high-volume work can be a distraction. Outsourcing during seasonal spikes may make perfect sense.
Be thoughtful about what work is completed where and by whom. Is it strategic? Does the organization gain institutional knowledge from the assignment? Does the task depend principally on internal information and decisions? Does the work require legal advice or just legal information? Perhaps a legal services provider is a viable alternative rather than a full-service law firm. These are other factors to consider when deciding who should complete work and what should be automated.
AI Needs Access To Business Data
For AI to perform reliably, it needs access to information. Providing access to commercial objectives, entity structures, historical matters, negotiation history, approval authorities, or prior legal positions will improve any AI solution. The problem is, many organizations don’t have systems to support this. This is more important than deploying the latest foundation model, which will change.
Information can live in many places and may not even sit in a system of record. Creating a data inventory and an architecture to support and organize it may be the best action a law department can take. Are contracts in a central repository and tagged appropriately? What about policies? Does the business’s CRM use the same customer naming convention as the procurement system does for suppliers? Are closed matters and disputes, including their outcomes, stored centrally? A data architecture ensures consistent metadata tagging, enabling AI to navigate data across systems and make good decisions. Are permissions in place to reflect privilege, confidentiality, and security?
Even AI needs to conform to those.
Palantir-style, forward-deployed engineers help ensure AI solutions have access to the underlying data. Omar Haroun, co-founder and CEO of Eudia, says, “Having forward-deployed teams on the ground helps bridge complex enterprise data silos, especially when building on top of a scalable platform layer. They can quickly connect your data, enforce security controls, and encode your custom risk profile directly into a repeatable architecture.”
Enabling AI to access data creates possibilities and makes projects that would previously have been unheard of feasible.
Without a data architecture, AI may simply accelerate poor decision-making.
Law Department 2.0 Is Optimized
The reimagined law department will organize knowledge and make it accessible. More tasks may belong within the business, while other work should be automated with agents or eliminated. Outsourcing to firms or legal service providers will be more thoughtful, based upon the need for outside expertise and the level of distraction.
Perhaps the biggest impact of AI is that it demands that assumptions are challenged.
Part II will examine what may happen downstream when the reimagined law department has greater control over its legal process.
Ken Crutchfield has over 40 years of experience in legal, tax, and other industries. Throughout his career, he has focused on growth, innovation, and business transformation. His consulting practice advises investors, legal tech startups and others. As a strategic thinker who understands markets and creating products to meet customer needs, he has worked in start-ups and large enterprises. He has served in General Management capacities in six businesses. Ken has a pulse on the trends affecting the market. Whether it was the Internet in the 1980s or Generative AI, he understands technology and how it can impact business. Crutchfield started his career as an intern with LexisNexis and has worked at Thomson Reuters, Bloomberg, Dun & Bradstreet, and Wolters Kluwer. Ken has an MBA and holds a B.S. in Electrical Engineering from The Ohio State University.
