Attorney-Client Privilege and AI
ETHICS
Does using AI put the privilege at risk? Covers the Kovel doctrine, U.S. v. Heppner (S.D.N.Y. 2026), ABA Formal Opinion 512, and a six-step privilege preservation framework attorneys can implement immediately.
Attorney Work Product Doctrine and AI
When AI-generated legal materials qualify as work product, when they do not, and how to preserve the protection. Covers Hickman v. Taylor, FRCP 26(b)(3), the adoption doctrine, and waiver scenarios.
Client Data Protection and AI
ETHICS
HIPAA Business Associate status, GDPR application to Montana firms, Montana MCDPA obligations, and a five-step breach response protocol. Covers Rule 1.6 as a data protection obligation, not just an evidentiary one.
AI Deployment Tiers
Why all AI is not the same. Covers five tiers - open source, consumer EULA, enterprise API, semi-sovereign, and sovereign - and the data classification gate that determines which tier your firm must use for each type of matter.
EU AI Act, U.S. Regulation, and ISO 42001
The EU AI Act's four-tier risk framework, extraterritorial scope for Montana firms, the current U.S. regulatory landscape, and how ISO/IEC 42001 aligns with ABA Opinion 512 and NIST simultaneously.
Shadow AI: The Hidden Risk
ETHICS
40-75% of professional workers use unauthorized AI tools. Covers Rules 1.6, 5.1, 5.3, 3.3, and 8.4 as applied to undisclosed AI use, five verified real-world incidents, detection methods, and a three-layer prevention program.
The Billable Hour and AI
ETHICS
Rule 1.5 reasonableness in the age of AI efficiency. Covers ABA Opinion 512 billing guidance, the efficiency paradox, five alternative billing models, engagement letter disclosure language, and a 90-day roadmap for fee structure transition.
The Attorney in the Loop
ETHICS
Rule 1.1 competence and the attorney's non-delegable professional judgment. Covers AI sanctions cases, Montana judicial AI disclosure requirements in Billings and Missoula, and the AITL framework as the minimum floor of professional competence in 2026.
Your Clients and AI
The client-facing dimension of AI governance. Covers handling AI-drafted client submissions, the five-step protocol for evaluating client AI documents, disclosure obligations when clients ask whether you use AI, and client data requirements.
AI and the Expert Witness
Disclosure requirements and Daubert challenges for AI-assisted expert opinions. Covers the first wave of court rulings, cross-examination techniques targeting AI expert use, and how to retain or challenge AI-assisted experts on both sides of the docket.
AI in Depositions
Real-time AI transcription and analysis tools in the deposition room, an updated opening stipulation framework, the five-question sequence for examining fact witnesses about AI use, and a 30(b)(6) framework for deposing AI decision-making systems.
AI Hallucination in Legal Practice
ETHICS
A seven-type taxonomy of AI hallucination failures, high-risk practice areas and tasks, detection and verification protocols, and the ethical duties under Rules 1.1, 3.3, and 5.3 triggered when AI fabrication reaches a client or a court.
Judicial AI Orders and Compliance
How to research, track, and comply with judicial AI requirements before every filing. Covers the four-category taxonomy of judicial AI orders, major federal district requirements, court-by-court compliance checklists, and sanctions exposure for non-compliance.
AI-Generated Evidence
A practitioner's framework for offering, opposing, and evaluating AI-generated evidence. Covers FRE 901 and 902 authentication, hearsay and best evidence issues, Daubert for AI forensic analysis, and strategy for challenging opposing AI exhibits.
Negotiating AI Vendor Contracts
What is actually in AI vendor agreements and what to demand. Covers seven categories of provisions that create unexpected exposure, a redline framework for data rights and training data clauses, SLA requirements, and audit rights for professional responsibility compliance.
AI in HR and Employment Law
Hiring algorithms, discrimination law, and the compliance obligations facing employers and employment lawyers. Covers Title VII disparate impact, the proxy variable problem, ADA obligations for AI screening, NYC Local Law 144, and NLRA workplace surveillance implications.
Intellectual Property and AI
Who owns what the machine creates. Covers the Copyright Office's human authorship doctrine, the Thaler line of cases, major training data litigation (Andersen, Getty Images), patent eligibility for AI-assisted inventions, trade secret protection, and trademark risk.
AI in Regulated Industries
Sector-specific compliance for healthcare, financial services, and defense contracting. Covers FDA's AI/ML SaMD framework, HIPAA and AI vendors, OCC Model Risk Management, CFPB adverse action notices, and DoD DFARS and CMMC requirements.
Building a Law Firm AI Committee
Charter, composition, decision rights, meeting cadence, and the governance infrastructure that makes AI programs durable. Covers the case for a standing AI committee, the tool approval registry, vendor review process, and incident response protocol for firms of every size.
The complete AI malpractice risk landscape. Covers Mata v. Avianca and subsequent sanctions decisions, Rules 1.1 and 5.3 verification obligations, FRCP Rule 11 sanctions exposure, professional discipline cases under Rules 1.1, 3.3, and 8.4, and a malpractice risk management framework.
AI at the Deal Table
Contract drafting, due diligence, and transactional practice in the AI era. Covers AI contract review tools, verification obligations for deal documents, client representations and warranties for AI use, privilege in virtual data rooms, and malpractice exposure when AI-assisted diligence misses a material issue.
AI in Criminal Law and Justice
The highest-stakes application of AI in the legal system. Covers predictive policing, algorithmic sentencing (State v. Loomis/COMPAS), Fourth Amendment and AI surveillance, Brady/Giglio disclosure for AI evidence, and the resource disparity between prosecution and defense AI access.
AI, Cybersecurity, and the Law Firm
Why law firms are high-priority targets and what AI has changed. Covers AI-powered spear phishing, BEC, and deepfake fraud, Rule 1.6 cybersecurity obligations, ABA Formal Opinion 483, breach notification requirements, AI defensive tools, and cyber insurance gaps in the AI era.
The DPA Imperative
Data Protection Agreements and why every AI tool your firm uses requires one. Covers GDPR Article 28, Montana MCDPA requirements, DPA vs. MSA vs. Privacy Policy distinctions, where DPAs are legally required, and the risk of operating without one in an AI-intensive practice.
