The fastest way to make AI adoption fail is to announce that the firm is “using AI” without defining what that means.

That approach produces inconsistent experiments, uneven quality, uncertainty about confidentiality, and a predictable divide between people who adopt a tool immediately and people who refuse to touch it. None of that is a strategy.

A better approach is a controlled 90-day pilot. The purpose is not to prove that AI can do everything. It is to determine whether one approved tool can improve one defined workflow without compromising client information, professional judgment, or work quality.

Part 1 of this series explained where AI fits in a law practice: as an assistant for organizing information, locating issues, comparing documents, and creating a reviewable first draft—not as a substitute for lawyer judgment. This article turns that principle into an adoption plan.

What a pilot should accomplish

A useful pilot answers five questions:

1. What problem are we trying to solve?

2. Which workflow will we test?

3. Who owns the process and reviews the output?

4. How will we protect client information and verify quality?

5. What evidence will tell us whether to adopt, revise, expand, or stop?

The firm should be able to describe the pilot in one sentence. For example:

“For 90 days, the litigation team will use an approved AI tool to create first-pass chronologies from produced records, with attorney review before the chronology is used in a client update, deposition plan, filing, or case strategy discussion.”

That is specific enough to manage. “We are going to use AI for litigation” is not.

Choose one workflow, not an entire practice area

The strongest pilot begins with a recurring bottleneck that the firm already understands. Good candidates include:

• producing first-pass chronologies from records, discovery, or client documents;

• summarizing long transcripts or document productions for attorney review;

• comparing versions of contracts or pleadings;

• preparing internal research outlines linked to verified authorities;

• creating internal intake summaries and missing-information checklists; or

• drafting routine internal or client communications from a lawyer-approved factual record.

The best use case is usually high-volume, repetitive, document-heavy, and reviewable. It should save time at the information-organization stage while leaving legal analysis, strategy, and final approval with people.

Avoid using the first pilot for the firm’s highest-risk work. Do not begin with unreviewed client advice, court filings, settlement communications, or a workflow that requires the system to make a legal, factual, or strategic decision on its own.

Build a small pilot team

AI adoption is not solely an IT project and not solely a lawyer project. The pilot team should include people who understand the workflow, the risk, and the day-to-day operational reality.

A practical team includes:

Role

Core responsibility

Attorney sponsor

Defines the legal use case, review standard, and client-service objective.

Workflow owner

Documents the current process, trains users, gathers feedback, and identifies friction.

Participating lawyers or staff

Use the tool in real but controlled work and report what works and fails.

Technology or security contact

Confirms that the selected platform is approved and that access and information-handling expectations are understood.

Final reviewer

Reviews a sample or all output, depending on the risk of the task, before the output is used beyond the pilot team.

The team does not need to be large. In fact, smaller is better at the beginning. A pilot with two to five regular users can generate clearer feedback than a firmwide launch with no defined accountability.

Days 1–30: define the process before measuring it

The first month is for setup. The firm should document how the work is completed today, choose the approved tool, establish guardrails, and set a baseline.

Map the current workflow

Ask the people who actually do the work:

• What begins the task?

• What source documents are required?

• Who performs the first review?

• What takes the most time?

• What mistakes or omissions occur most often?

• What must be checked before the result is used?

• What does a successful output look like?

The goal is to understand the current process well enough to compare it with the pilot process. Without a baseline, “AI saved time” is only an impression.

Set the rules before use begins

The pilot should have a short written protocol that answers:

• which tool is approved;

• which matters or documents may be used in the pilot;

• what information requires additional review before submission to the tool;

• who has access;

• what output requires attorney review;

• where final work product is stored; and

• who should be notified if the tool produces an unsupported citation, a factual error, a confidentiality concern, or an unexpected result.

The protocol does not need to be a 30-page policy. It does need to be clear enough that participants do not invent different rules for themselves.

Days 31–60: run real work through a controlled process

The middle of the pilot is where the firm tests whether the workflow works in practice.

Participants should use the tool on genuine matters within the approved scope. But the pilot should still include a human checkpoint before any output becomes client work product, informs a legal strategy decision, or is filed with a court.

A simple workflow might look like this:

1. A participating user prepares the approved source materials.

2. The user runs the defined task through the approved platform.

3. The user reviews the output against the source documents.

4. The designated attorney or reviewer checks the output at the level appropriate for the task.

5. The team records the time spent, corrections made, and any issue encountered.

6. The final approved work product is saved through the firm’s normal matter-management process.

This stage should test actual work, not demonstrations. A tool may look impressive on a clean sample document and still be unhelpful when it encounters incomplete records, scanned PDFs, inconsistent dates, multiple parties, or a messy production. That is precisely what the pilot needs to reveal.

Train for judgment, not prompts

Training should focus less on clever instructions and more on professional use.

Participants should understand:

• the purpose and limits of the selected workflow;

• the source materials the tool is—and is not—receiving;

• how to ask the tool to identify uncertainty rather than invent an answer;

• how to verify facts, citations, calculations, and quotations;

• when a result should be escalated to an attorney or the pilot owner; and

• why unreviewed output cannot be sent to a client or filed with a court.

The most important training message is this: a polished answer is not necessarily a correct answer. The reviewer’s job is to confirm the result, not merely improve its wording.

Days 61–90: measure the results and decide what happens next

The final month should not be a victory lap. It should be a candid evaluation.

A useful pilot measures more than raw time savings. Firms should ask whether the process improved the work, improved the client experience, and fit the firm’s risk controls.

What to measure

Measure

Why it matters

Time to complete the task

Shows whether the workflow actually reduces effort or simply moves it to review.

Time spent on review and correction

Identifies whether the first-pass output is reliable enough to be useful.

Completeness of the output

Tests whether the tool surfaced the dates, issues, documents, or differences the reviewer needed.

Error type and frequency

Reveals whether errors are minor formatting problems or material factual, legal, or confidentiality concerns.

User adoption and feedback

A process that no one will use consistently is not ready to scale.

Client-service effect

Consider turnaround time, responsiveness, and whether attorneys gained time for counseling and strategy.

Risk-control performance

Confirms whether users followed the protocol and whether human review caught problems before external use.

The firm does not need a perfect dashboard. A short scorecard completed after each pilot task can be enough to identify the trend.

The scale-or-stop decision

At the end of 90 days, the pilot team should recommend one of four outcomes:

• Adopt: The workflow improved speed or quality, the review process worked, and the risks were manageable.

• Revise: The use case is valuable, but the protocol, training, source preparation, or review expectations need adjustment.

• Expand carefully: The workflow should move to another team or matter type, but with the same controlled process and measurement.

• Stop: The workflow did not create enough value, could not be verified efficiently, or created risks the firm could not adequately control.

Stopping a pilot is not a failure. It is evidence that the firm tested a process before making a larger investment or exposing client work to an unproven workflow.

Common mistakes to avoid

Starting with a tool instead of a problem

A firm may buy an AI product because competitors are discussing AI, then search for a reason to use it. That reverses the process. Define the workflow problem first.

Measuring only speed

A faster first draft is not useful if it creates more review work, misses material information, or confuses the client. Measure quality and review burden along with time.

Treating all work as equally risky

A first-pass chronology and a client-facing legal opinion do not require the same approval process. The firm should match supervision to the nature of the work.

Assuming adoption will happen by announcement

People need a defined task, brief training, an approved tool, a person to ask when something goes wrong, and a reason to believe the process will make their work better.

Failing to capture lessons

A pilot should create a reusable playbook: what source materials worked best, what review was needed, what errors occurred, and what instructions or safeguards improved the result. Otherwise, each new team begins from zero.

The real goal: better professional time

A good AI pilot is not about proving that a machine can write. It is about proving that the firm can use technology to reduce low-value friction while preserving the parts of legal practice that require professional responsibility.

If a tool shortens the time needed to organize records, compare documents, or prepare a reviewable first draft, the lawyer can spend more time asking the question that matters: what should the client do next?

That is the standard for success. Not more output for its own sake. Better use of trained people, better responsiveness, and better service to clients.

Bottom line

A 90-day pilot gives a firm a disciplined way to move from curiosity to evidence. Choose one use case, limit the participants, use approved technology, require human review, measure the result, and decide whether to adopt, revise, expand, or stop.

The next article in this series will address the governance layer that makes responsible adoption sustainable: confidentiality, privilege, vendor diligence, source verification, and internal quality-control rules.

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.

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.

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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.

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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.