Practical automation for professional firms — deployed so that regulated data never leaves your control.
Your staff are already using AI tools. In most firms we assess, someone has pasted a client document into a consumer chatbot — not maliciously, but because it saved forty minutes and nobody said not to.
For a firm holding PHI or privileged client material, that is the exposure that matters. It is not a hypothetical about model behaviour; it is regulated data leaving your control through a tool with no BAA, no retention guarantee and no audit trail. The fix is not banning AI, which does not work. It is providing a sanctioned path that is easier than the unsanctioned one.
We are deliberately narrow about this, because most AI pilots in small firms fail for the same reason: they automate something that was not a bottleneck.
Routing inbound enquiries, extracting structured detail from unstructured messages, and getting the right matter to the right person without a human reading everything first.
Summarising and classifying documents at volume — the work that is high-effort and low-judgement, where a human reviews the output rather than producing it.
First drafts of routine correspondence and recurring reports, always with a named human accountable for what goes out.
Answering staff questions against your own documented procedures, so institutional knowledge is not held in one person's memory.
Automation is worth it when a process is high-volume, rule-shaped and low-judgement. It is not worth it when the process runs a handful of times a month, when the judgement is the actual work, or when the input is too inconsistent to structure.
We would rather scope you out of a project than sell an automation that adds a review burden heavier than the work it replaced. That happens more often than the market admits.
AI governance is a compliance question as much as a technology one — see compliance services. For law firms specifically, see AI automation for law firms. For whether a given tool can hold regulated data, see our tool-by-tool compliance guides.
It depends entirely on the tool and its contract. A tool operating inside your Microsoft 365 tenant under an existing BAA is a different proposition from a consumer chatbot with no agreement, unclear retention and no audit trail. Before any AI tool touches regulated data, three questions need answers: will the vendor sign a BAA, does it train on your inputs, and how long does it retain them.
A chatbot responds to a prompt and stops. An agent takes actions across systems to complete a task — reading a mailbox, updating a record, triggering a workflow. The distinction matters for risk, because an agent needs permissions, and permissions granted to software need the same access review as permissions granted to a person. Most firms should start with the former.
In firms your size, the honest answer is no — it removes specific low-judgement tasks from people who are already at capacity. The realistic gain is throughput on routine work, not headcount reduction. Anyone promising staff replacement to a twelve-person practice is selling something.
It varies with the process, but the dominant cost is rarely the technology — it is mapping the current process accurately enough to automate it. Most firms discover their process is not documented anywhere and works differently depending on who runs it. That discovery is valuable on its own, and it is why we scope one workflow at a time.
Yes, and it is usually the first thing we do, because staff are already using these tools whether a policy exists or not. A workable policy names the approved tools, states plainly what must never be entered into them, and assigns accountability for reviewing output before it leaves the firm.
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