Artificial intelligence is already part of legal work. The question for law firms is no longer whether someone in the firm will try it. The more useful question is whether the firm will use it deliberately, securely, and in ways that improve client service.
The answer is not to hand legal judgment to a machine. It is to identify the work that consumes professional time without requiring a professional to start from a blank page every time: organizing information, locating issues, comparing documents, building chronologies, identifying patterns, and producing a first-pass draft for lawyer review.
That distinction matters. The goal is not to replace lawyers. The goal is to give lawyers and staff more time for the work clients actually need from them: judgment, strategy, counseling, advocacy, negotiation, and accountability.
Start with the work—not the technology
A common mistake is to begin with a general instruction to “use AI.” That produces scattered experimentation and inconsistent results.
A better starting point is a workflow question:
What recurring task is slowing the team down, delaying the client, or consuming time that could be spent on higher-value legal work?
The best early use cases usually have three characteristics:
They recur often. The firm encounters the same task across many matters.
They involve a large volume of information. Someone must read, sort, compare, or summarize material before legal analysis can begin.
They remain subject to human review. The output can help a lawyer or trained staff member work faster, but it does not become the final answer without verification.
This framework shifts the conversation from “What can this tool do?” to “What bottleneck can we responsibly improve?”
Where AI can add practical value
Organizing facts and documents
Legal teams routinely receive information in forms that are hard to use: long emails, scanned records, police reports, discovery productions, financial statements, medical records, contract versions, and client-uploaded documents.
AI can help create a first-pass summary, chronology, issue list, or document inventory. That does not eliminate the need to read key records. It gives the reviewer a structured starting point and helps identify what deserves closer attention.
Examples include:
building a chronology from pleadings, correspondence, records, and reports;
identifying dates, people, documents, and events that recur across a production;
summarizing a deposition or hearing transcript for attorney review; and
preparing a document checklist that identifies missing or inconsistent information.
Research preparation and source organization
AI can help lawyers formulate research questions, identify potentially relevant authorities, summarize long opinions, and organize a first-pass discussion of competing arguments.
The lawyer remains responsible for verifying the authority, checking that a case remains good law, reading the opinion in context, and deciding whether the authority supports the position being advanced. AI can accelerate the path to those tasks; it cannot replace them.
Drafting from a verified factual record
Once facts, objectives, and governing law are confirmed, AI can assist with first drafts of routine communications, internal summaries, issue lists, document requests, outlines, and other work product.
The safe and useful model is not “generate and send.” It is generate, review, revise, and approve. A lawyer or appropriately supervised professional must confirm that the draft reflects the actual record, client instructions, applicable law, tone, and strategic purpose.
Comparing and reviewing documents
Many transactional and litigation tasks begin with comparison: what changed between two versions, what terms appear in each agreement, which provision is missing, or where a document conflicts with another record.
AI can rapidly surface differences and recurring provisions. That can reduce the time spent locating the issue, allowing the lawyer to focus on the harder question: whether the difference matters, what risk it creates, and what should happen next.
Where AI does not belong alone
AI is not a lawyer, a client representative, or the person accountable for the matter. There are tasks that cannot be delegated to an automated system.
Legal judgment and client advice
An AI system cannot decide what a client should do. It cannot assess the client’s risk tolerance, business priorities, family circumstances, credibility, litigation posture, or goals. Those decisions require a lawyer’s judgment and a real attorney-client relationship.
Final verification of facts and authorities
AI output may omit a fact, misunderstand a document, use an outdated authority, or state a proposition too broadly. Every material fact, citation, quotation, calculation, and legal proposition requires human verification before it is relied upon or sent outside the firm.
Strategic decisions
Whether to file a motion, accept an offer, initiate settlement discussions, take a deposition, advise a client to testify, or pursue a particular claim is not an automation problem. AI may help organize information relevant to the decision, but the decision belongs to the lawyer and client.
Client communication without review
Clients should not receive unreviewed AI-generated legal advice, case updates, or draft documents. A fast response is valuable only if it is accurate, understandable, appropriately tailored, and consistent with the client’s objectives.
The human-review rule
The most useful internal rule is also the simplest:
No AI output becomes client work product until a qualified human reviews it.
That rule should apply whether the output is a summary, research result, chronology, contract comparison, draft letter, internal memorandum, or client-facing communication.
Human review is not a ceremonial final glance. It should be matched to the risk of the task. A routine internal document list may require a different level of review than a court filing, legal memorandum, settlement communication, or advice that could affect a client’s liberty, livelihood, family, or business.
The reviewer should be able to answer:
What source material supports this statement?
Is the output complete enough for its purpose?
Does it reflect current law and the actual facts of the matter?
Does it reveal confidential information or create a misleading impression?
Is this the advice, analysis, or communication the client should receive?
Choosing the first use case
Firms do not need to transform every workflow at once. In fact, they should not. A controlled first use case is better than a broad, unmeasured rollout.
A good first project might be:
first-pass summaries of incoming client documents;
chronologies from records or productions;
comparison of contract versions;
internal research outlines that link to verified authorities;
checklists for recurring intake or closing tasks; or
internal drafts of routine correspondence for lawyer review.
A poor first project is one where the firm cannot describe the expected result, identify a reviewer, define approved information sources, or measure whether the new process improved anything.
A five-question test
Before adopting AI for a workflow, ask:
Is the task repetitive? Repetition makes it easier to define a useful, reliable process.
Is the source material available and appropriate for the approved tool? The firm must understand what information will be used and how it will be protected.
Can a human verify the output efficiently? If verification takes as long as doing the work from scratch, the use case may not be ready.
Is the output a starting point rather than an unreviewed final answer? The firm should retain lawyer judgment and accountability.
Can the firm measure the result? Track turnaround time, completeness, error correction, client response, and user feedback.
The ethical question is not whether to use AI
The ethical question is whether the firm is using technology competently and responsibly.
That means understanding the tool well enough to recognize its benefits and limitations; protecting client information; supervising the work product; checking sources and facts; and ensuring that a lawyer remains accountable for legal services.
Firms should resist two unhelpful instincts. The first is to prohibit all AI use and assume the issue will disappear. The second is to allow uncontrolled use and assume the technology will police itself. Neither approach creates a durable professional workflow.
A responsible firm starts small, uses approved tools, establishes review expectations, and learns from the results. The next post in this series will address how to turn that first controlled use case into a structured 90-day pilot.
Bottom line
AI is most useful when it helps a legal team move from unstructured information to an organized starting point. It can make document-heavy work faster, help lawyers find issues sooner, and create capacity for better client communication and more deliberate legal judgment.
But AI does not relieve a firm of its professional duties. The lawyer remains responsible for the facts, law, strategy, advice, and final work product.
The right first step is not to ask AI to run the practice. It is to identify one recurring task where AI can assist a trained professional, build a review process around it, and measure whether the client and the firm are actually better served.
This article is for general informational purposes only and is not legal advice. Firms should evaluate their own professional obligations, client-information practices, approved technology, and supervision procedures before implementing an AI-assisted workflow.