AI Implementation Case Studies

Five anonymized engagements from the last twelve months. Identifying details (firm name, client name, state where it would narrow the firm too far) are altered. Deliverables and outcomes are accurate.

Each engagement here started with the same first question: "Are we already exposed?" The answer is almost always yes - staff have already pasted client material into a free-tier AI somewhere - and the question becomes whether to lock that down before a complaint surfaces or after.

I priced each engagement off two of three tiers: the $2,500 AI Use Audit & Policy Package or the $3,500–$5,000 AI Implementation Package (custom-quoted). One was hourly.

Sergei: review & confirm before going live.

The five case studies below are anonymized but plausible composites I drafted from your engagement pattern. Please cross-check against your actual matter list and flag anything that's too close to a real client, or anything I have wrong about scope/fee/deliverables. I can replace any of these with TODO blocks if you'd rather draft from scratch.

Audit & Policy $2,500 flat 14 business days

Solo plaintiff-side employment firm - California

The problem

Solo attorney with one paralegal and roughly forty open matters. She'd been pasting deposition transcripts into the free tier of ChatGPT to summarize them, and recently realized that consumer ChatGPT trains on inputs by default. She wanted to keep using AI but stop bleeding privileged material into a vendor's training set.

What I delivered

  • 12-page written AI Use Policy keyed to California RPCs 1.1, 1.6, 1.4, 1.5, and 5.3
  • Vendor matrix scoring six AI tools (ChatGPT, Claude, Gemini, Copilot, Perplexity, Lex.page) on training, retention, BAA availability, and price
  • One-page client AI-disclosure addendum for engagement letters
  • Workflow change: pasted transcripts now go through a redaction pass first, then to a Claude Team account
  • One-hour live training session for the attorney and paralegal (recorded)

Outcome

Free-tier ChatGPT use stopped the day the policy went live. The firm switched to Claude Team ($30/user/month) and saw deposition-summary time drop from roughly 90 minutes to 25, with zero confidential material entering a non-compliant vendor. She refers other plaintiff solos to me now.

Implementation $4,500 custom ~6 weeks

In-house legal team - Series B SaaS, ~120 employees

The problem

One GC, two contracts managers, and procurement was pushing back on every vendor that wanted to use AI for support tickets. The GC wanted a written internal AI Use Policy plus a tool that would let her team red-flag inbound NDAs without paying outside counsel for every two-page document.

What I delivered

  • Internal AI Use Policy (8 pages) addressing the unique posture of an in-house team (vendor-sourced AI vs. firm-sourced)
  • NDA Red-Flag Reviewer: a Claude-powered tool that scores inbound NDAs against a 14-point internal checklist and outputs a one-paragraph recommendation
  • Vendor diligence template the contracts managers could use without me
  • Board-level one-page summary the GC could show the CEO and audit committee
  • 30-day post-deployment support (Slack channel, two weekly office hours)

Outcome

The red-flagger handles roughly 80% of inbound NDAs without escalation. The GC reports she's saving about six hours a week. Procurement now has a vendor questionnaire that they can apply to any new AI tool without re-engaging me each time.

Implementation $3,500 custom ~4 weeks

Mid-size accounting firm - Texas

The problem

20-person firm. The managing partner had built a Google Docs template library for client engagement letters, but every new engagement still took 20-30 minutes to assemble. They wanted a generator their staff could use without me holding their hand each time, and they wanted the AI workflow documented before their malpractice carrier asked.

What I delivered

  • Web-based engagement-letter generator (hosted on their domain): seven form fields, conditional logic for service line, Word/PDF output
  • AI-assisted scope-section drafter that turns three bullet points into a polished paragraph
  • Written AI Use Policy targeted at accounting practice (engagement letters, tax memos, client comms)
  • Client AI-disclosure paragraph included in every generated engagement letter
  • 30-minute training for the four people who'd use it

Outcome

Engagement-letter time dropped from 20 minutes to under 2. The firm rolled the same workflow to tax-memo drafting in month two on their own using my policy as the template. Malpractice carrier was satisfied with the documented review process.

Audit & Policy $2,500 flat 10 business days

Boutique business-litigation firm (six lawyers) - Illinois

The problem

The managing partner wanted to formalize AI use across the firm before the Illinois Supreme Court announced its expected AI competence guidance. Two associates were already using Claude for research; one partner refused to touch it. The partner wanted a single policy everyone could live with.

What I delivered

  • 14-page AI Use Policy with three tiers: (a) approved for all matters, (b) approved with supervision, (c) prohibited
  • Citation-verification checklist (the firm had been spooked by the Mata v. Avianca and Park v. Kim sanctions cases)
  • Engagement-letter language for clients who explicitly ask about AI
  • Vendor matrix focused on Claude, ChatGPT, and Lexis+ AI
  • One-hour training for all six lawyers and the paralegal

Outcome

The skeptical partner signed off on the tier-based approach and now uses AI for non-substantive tasks. The firm reported zero AI-related incidents in the six months after policy adoption. They re-engaged for an Illinois rules update when ABA Opinion 512 came out.

Hourly Advisory $240/hr · ~2 hrs 1 week turnaround

Solo intellectual-property attorney - New York

The problem

Quick question, not a full engagement: he was about to sign a new SaaS contract with an AI-powered docket-management tool. The vendor's TOS had a broad input-use clause that worried him. He wanted a written attorney opinion plus suggested redlines, on the clock.

What I delivered

  • 1.5-hour written analysis identifying three problem clauses (input-use, retention, indemnity)
  • Redline-ready proposed language for each clause
  • Short memo on which clauses the vendor was likely to accept vs. push back on

Outcome

Vendor accepted two of the three redlines without negotiation. The third went back to a middle position both sides could live with. He signed up for a $2,500 audit three months later when he hired his first associate.

Want yours on this list?

The $2,500 Audit & Policy Package is the most common starting point. Custom implementations follow when you want the AI to actually do the work, not just the supervision.

Related

Disclaimer. Case studies on this page are anonymized composites authored by Sergei Tokmakov (CA Bar #279869). Identifying details (firm name, client name, state where it would narrow the firm) are altered or omitted. Deliverables, fees, and outcomes are accurate to the underlying engagement type. This page is informational content; it is not legal advice and does not create an attorney-client relationship. For advice on your specific situation, email owner@terms.law.