Pittsburgh 32-Attorney Firm: 10-Week AI Governance Build — Assessment Revealed 14 Attorneys and 6 Paralegals Using Consumer AI on Client Matters

A Pittsburgh-based managed services provider published July 16 a detailed case study of a 10-week AI governance engagement with a 32-attorney litigation and transactional firm downtown — one of the most practically specific mid-sized firm AI governance cases documented this year. The assessment phase (Weeks 1–2) used endpoint telemetry and interviews to map which AI tools were actually in use, which matters they had touched, and what data categories were exposed: 14 of 32 attorneys and 6 of 11 paralegals were using AI tools on firm devices, including free consumer-grade chatbots and ChatGPT. A Slack message from an associate noting she had been "using ChatGPT to summarize depositions" was the trigger that revealed potentially privileged content had been pasted into a consumer chatbot with no data boundary controls. The firm's governance response was structured in four layers: a written generative AI policy reviewed by outside ethics counsel (referencing PA RPC 1.1, 1.6, 1.5, and 5.3, and ABA Formal Opinion 512), deployment of Microsoft 365 Copilot with tenant-level data-boundary controls and a legal-specific research assistant with no-training contractual terms, consumer AI blocked at network and endpoint layer with DLP rules preventing privileged documents from reaching unapproved web destinations, and role-based training with signed attestations from all timekeepers. Outcomes: 100% training completion, every unsanctioned AI tool retired, two enterprise-client policy requests closed, and a written AI governance program the managing partner could hand to any client, auditor, or malpractice carrier. For IT directors and managing partners at mid-sized firms, the Pittsburgh case is a replicable template — the engagement confirms the shadow AI problem is not a BigLaw problem, and the governance build is achievable inside a quarter.