How law firms can put AI to work without hiring a legal engineer
Suppose your team is waiting on documents from a client before a matter can move forward. One file arrives by email, another is uploaded later, and a third is still missing. Someone checks what came in, updates the matter and follows up. A few days later, someone may have to check all over again.
That work can be handled through an agreed workflow. It checks incoming documents against your checklist, keeps track of what's missing and prepares a follow-up. Your team reviews the request before it goes out. After approval, the message is sent through the agreed process, and the request remains open until the missing items are received and checked.
Your firm helps get the process right. A managed service can build the automation, keep it working and bring your people in when their review or judgment is needed. You can start without adding a full-time legal engineer to your staff.
What does a legal engineer do?
Legal engineers combine knowledge of legal work with technology and process design. Depending on the role, they may develop workflows, help lawyers use AI tools or train colleagues. Many are former practicing attorneys; others have backgrounds in legal operations or technology.
In an October 2026 article, The New York Times described legal engineers working at law firms, legal technology companies and corporate legal departments. Some help customers fit a company's AI products into their work. Others work inside a firm on processes across its practices.
How would a managed service handle the work?
At SubAI, we start with the work your firm wants to improve. Our law firm workflow library gives us examples to discuss, and your team helps us understand how the process should work in your practice. We also check what your current software can do before recommending additional automation.
Consider the document collection example above. A paralegal or attorney could help us establish which documents belong on the checklist and how the firm checks them. We would also agree where to look and who approves a request. Together, we would test examples your firm authorizes, including a document that has already arrived and a file that may be the wrong version. The team's feedback helps us correct the workflow before it goes into operation.
Once it is running, SubAI manages the agreed automation. If a connection fails, we investigate it. When the firm's process changes, we work with the firm on the updates within the agreed scope. An uncertain document match stays open for the person your firm designates. Your staff can review messages or documents when needed, while we handle the technical work behind the process.
The result should be visible. For document collection, a firm could track requests resolved, repeated requests for documents already received and staff time spent checking and following up. A request awaiting review or a client's response stays open; it is not counted as completed. To estimate staff time released, include the time still spent on review, corrections and exceptions. Our article on turning time saved by AI into business value explains how to assess what that capacity makes possible.
Where else could it help?
Document collection is one place to start. The following are examples to explore with your firm. What we agree to build depends on your priorities, the systems you use and the review steps the work requires.
- Intake and follow-up: check for unanswered inquiries, confirm their current status and prepare follow-up for the designated person to approve. The workflow can track the next step after approval.
- Legal work: compare an incoming agreement with standards approved by the firm's attorneys and bring possible differences, alongside the relevant language, to an attorney for review. The attorney evaluates the findings and decides what advice to give.
- Matter administration: once a lawyer approves a matter for closing, check the firm's closing checklist, prepare the agreed administrative steps and track outstanding items.
Where does your firm stay involved?
Your firm and SubAI agree on which steps can run under approved rules and which need a person's approval or professional judgment. Your staff does not have to watch the connections or maintain the automation; that is part of the agreed service. SubAI reports what completed, how it performed and what needs attention.
Before client information is used, the firm and provider should agree how it will be handled, which tools can process it and who can access it. The American Bar Association's Formal Opinion 512 discusses confidentiality and lawyers' other responsibilities when using generative AI. Your attorneys retain the legal decisions and professional responsibilities that belong to them.
How does the cost compare with hiring?
The Times reported that Gibson Dunn advertised a legal technology and AI attorney role at $250,000 to $300,000 a year. Gibson Dunn's listing describes a litigation position requiring a law degree and admission to practice. It is one role at one firm; salaries for legal engineers vary.
A typical first SubAI engagement is $5,000 per month. At that rate, 12 billed months would be $60,000 in recurring service fees. For the first build of a standard engagement, we agree on a success test in writing before building, including the target and measurement period. The build and proving period are unbilled, and monthly billing begins when that workflow passes its test.
The $2,000 diagnostic is separate and is credited in full toward the first month if the build starts within 30 days. Industry-specific diligence, where needed, is a separate scope and price. Your proposal sets the scope and monthly price. You can review SubAI's pricing and engagement terms.
A full-time attorney can bring legal expertise, dedicated availability and responsibilities across a firm. SubAI manages the work in its agreed scope, with the firm's people providing the legal expertise and approvals the workflow needs. When comparing the options, account for the scope of work, any required software and the time your staff will spend participating.
Start with one piece of work
Bring a recent example of a process your team handles repeatedly and would like to improve. We will look at what already happens in your software, where the work waits and whether there is a useful first workflow to pursue. A discovery call helps determine whether a paid diagnostic makes sense. You can also see how SubAI approaches law firm automation.
For a closer look at your existing software, read what to check if your firm already has Clio AI. The document intake checklist covers what to settle before automating document collection.