How do you implement legal AI in a mid-sized law firm?
To implement legal AI in a mid-sized law firm, start with one practice group and one type of document, pilot the tool on live matters for a few weeks, agree a short AI use policy and review rule, then widen it only once the pilot group is using it without being chased. Most rollouts that stall do so because they start firm-wide, with no clear owner and no agreed precedents.
A firm of 20 to 100 fee earners rarely has an innovation team or a full-time knowledge lawyer. That is not a disadvantage. It means the rollout can be shorter and closer to the work, provided someone decides what "working" looks like before the licences arrive.
What is the best way to implement legal AI in a law firm?
Narrow first, then wide. Pick the work where a better first draft saves the most partner and associate time, prove it there, and let the results make the case to the rest of the firm.
The five steps below are the ones we would follow at any transactional firm, whichever tool it chooses.
- Choose one practice group and one document type. Corporate and share purchase agreements, commercial and supply terms, or real estate leases all work. The narrower the start, the faster you learn.
- Get the precedents in order. Agree which templates and standard positions are current. A tool that drafts from your precedents is only as good as the precedents it is given.
- Pilot on live matters. Run it for a few weeks with a small group, including at least one partner, on real work rather than test documents.
- Set the rules. Approve the tool, write a short AI use policy, and make lawyer review of every output a fixed step before anything goes to a client or the other side.
- Widen deliberately. Add the next practice group only when the pilot group uses the tool unprompted, and carry over what you learned about precedents and training.
How long does a legal AI rollout take at a mid-sized firm?
Usually weeks for a pilot and a few months for the whole firm. The software is rarely the slow part; agreeing precedents, policy and data protection sign-off usually is.
| Stage | Who is involved | What done looks like |
|---|---|---|
| Scope | Sponsoring partner, operations | One practice group, one document type, a named owner |
| Due diligence | Risk and compliance, IT | Security questions answered, data protection assessment done, policy drafted |
| Pilot | Three to six fee earners, one partner | Tool used on live matters, issues and gaps logged |
| Review | Sponsoring partner, pilot group | Decision to widen, adjust or stop, based on the pilot's evidence |
| Rollout | Next practice groups | Training done, precedents loaded, regular use without chasing |
An illustrative plan, not a fixed timetable. Firms with tidy precedents and an existing AI policy move faster.
The firms that adopt legal AI well do not buy the most licences. They pick the narrowest useful start and finish it.
Who should own the rollout?
A partner who does the work, not only someone from IT. Fee earners take their lead from how partners use a tool, so a sponsoring partner who drafts with it carries more weight than any training session.
Pair that partner with someone from operations or IT for set-up and with whoever handles risk and compliance for policy. Our post on getting a sceptical team to adopt legal AI covers the people side in more detail.
What policies and checks do you need first?
An approved-tools list, a short AI use policy, and a rule that a qualified lawyer reviews every output. Those three cover most of what a regulator or a client's panel questionnaire will ask.
For a UK firm, the policy should reflect your professional duties and data protection obligations: what client information can go into the tool, where it is stored, and whether the vendor uses it to train models. Our guides on how to write an AI use policy for your firm and GDPR and legal AI set out what to include.
How do you know the pilot has worked?
Look at whether the work got easier to supervise and faster to turn round, not only at hours saved. A good pilot ends with fee earners reaching for the tool without being reminded.
- First drafts need less reworking to reach the firm's house style.
- Partners spend their review time on judgement, not on fixing defined terms.
- Turnaround on the chosen document type is shorter for clients.
- The group keeps using the tool after the pilot formally ends.
We have argued before that hours saved is the wrong metric on its own; capacity and consistency tell you more.
Does the choice of tool change the rollout?
Yes, mainly in how much behaviour you are asking lawyers to change. Broad platforms such as Harvey and Legora cover research, litigation and transactional work, and can suit firms that want one tool across every practice. Microsoft Copilot sits across the whole Microsoft 365 suite. Specialist tools such as Spellbook and Scriptum AI focus on contracts.
For a transactional firm, a tool that works inside Microsoft Word and drafts from your own precedents usually asks the least of lawyers, because the drafting habit does not change. Our guide to the best legal AI for mid-sized UK law firms compares the options fairly.
How does Scriptum AI fit a mid-sized rollout?
Scriptum AI is built for transactional firms of 20 to 100 fee earners. It runs as a Microsoft Word add-in, drafts from your firm's own precedents, and builds a clause library your firm owns as matters move forward, with partner approval before anything is released. Your data is never used to train models. The Firm plan includes onboarding of your existing precedents and playbooks by practice area, which suits a group-by-group rollout. See the Draft product page for how drafting works.
Planning a pilot? Book a demo and we will walk through a live matter with you and suggest where to start.
Common questions
How long does it take to implement legal AI in a law firm?
For a mid-sized firm, a focused pilot in one practice group can run in a matter of weeks, and a firm-wide rollout over a few months. The timeline depends more on how quickly you agree policy and precedents than on the software.
Who should lead a legal AI rollout at a mid-sized firm?
A partner who does the work, supported by someone from IT or operations and the person responsible for risk and compliance. A partner sponsor matters because fee earners follow how partners actually use the tool.
Do we need an AI use policy before we start?
Yes, even a short one. It should say which tools are approved, what client information can go into them, and that a qualified lawyer reviews every output before it leaves the firm.
Should in-house legal teams roll out legal AI the same way?
Mostly. In-house teams usually start with the contracts they see most, such as NDAs or supplier agreements, and measure success by turnaround time for the business rather than by fee-earner capacity.
How does Scriptum AI help with implementation?
Scriptum AI works as a Microsoft Word add-in, so lawyers draft in the tool they already use, from the firm's own precedents. On the Firm plan, onboarding of your existing precedents is included.