The real cost of DIY AI inside a law firm

The cost categories

A simple way to estimate it

1. List the hours you expect to spend on build, testing and policy. Price them at your own opportunity cost, not a salary.
2. Estimate the weekly time saved after review, honestly.
3. Divide: how many weeks until savings repay the build? If it is more than a few months, reconsider.
4. Add an owner and a quarterly review date, or the workflow decays.

You can try the arithmetic with our calculators hub at /calculators, which includes tools for comparing practice-management costs. These calculators use your own inputs; we provide no benchmark figures.

When DIY is a good idea

• The task is narrow and repeated, such as summarising your own meeting notes or drafting routine client emails.
• The data is low sensitivity, or the tool's terms clearly fit your duties.
• A lawyer will always read the output before it leaves the firm.
• You can describe the workflow in a page, so someone else could run it if you left.

When to buy or keep it simple

If the workflow touches privileged material at volume, needs auditing or integrates with court or accounting systems, a vendor with proper contractual terms may be safer than a home-built chain of tools. Equally, many firms will find the best value in organising their matters and tasks cleanly first, because AI over messy data is expensive.

That is the thinking behind LawyerOS ($19 Starter or $39 Pro with AI, one-time): structured databases first, optional Notion AI use second. It is a template, so the firm still owns the supervision and policy.

Frequently asked questions

Is DIY AI cheaper than buying a legal AI product?

Not necessarily. The visible cost is lower but the build, review and maintenance time can exceed a vendor fee. Count your own hours.

Who should own AI workflows in a small firm?

A named lawyer, with a written note of the workflow, its approved data and its review step.

Do free tools have costs?

Yes: review time, data risk and possible changes to terms.

How often should we review AI workflows?

At least quarterly, and whenever a tool or its terms change.