Litigation AI GRC Briefings & Analysis for Law Firms

The October 15, 2026 Thursday review: ten developments across AI models, agents, infrastructure, commerce and media, with availability limits, independent evidence and practical enterprise and SME governance questions.

Join Pouya Shafabakhsh and Alexander Paykin for NYSBA’s October 22 AI workflow webinar. Explore the program, CLE credit, pricing and registration.

Radsam Academy of AI examines NYC’s proposed AI-misuse claim and a practical safeguards decision record for general counsel and product teams.

This week's priority is to connect AI-assisted work with verifiable sources, accurate system descriptions, and accountable decisions. A new SDNY fee award shows the continuing cost of citation misconduct, while proposed liability, disputed claims, appellate warnings, and regulatory communication require different responses. For Ontario and New York litigation leaders, the practical task is to identify the applicable authority, responsible reviewer, and evidence needed before

EXPERT OPINION By Pouya Shafabakhsh As legal AI moves from producing answers to completing multi-step work, end-stage review may come too late. Human approval should sit immediately before actions that create material or hard-to-reverse consequences. Reprinted with permission from the September 24, 2026 edition of the “Legaltech News” © 2026 ALM Global Properties, LLC. All rights reserved. Further duplication without permission is prohibited, contact 877-256-2472 or...

An expert may write every sentence and still rely on a record that artificial intelligence helped select. By Pouya Shafabakhsh Reprinted with permission from the September 29, 2026 edition of the “New York Law Journal” © 2026 ALM Global Properties, LLC. All rights reserved. Further duplication without permission is prohibited, contact 877-256-2472 or asset-and-logo-licensing@alm.com. Consider a lost-profits dispute in New York’s Commercial Division. The damages expert writes

Quebec’s new judicial guidelines offer an occasion to examine how AI assistance enters a litigation file, without confusing judicial guidance with lawyers’ duties. By Pouya Shafabakhsh This article was originally published by Law360 Canada (LexisNexis Canada Inc.) on September 23, 2026. Read the original article on Law360 Canada. A Quebec litigation team receives an English summary of French correspondence shortly before filing. The prose reads well. Yet a witness’s uncertain

This briefing examines ten AI-related developments reported or made public between September 28 and October 5, 2026. The central message is practical: courts, legislatures and copyright owners are not treating AI as a substitute for accountable professional judgment. The strongest developments this week involve verification of AI-assisted filings, ownership of training material, lawyer-specific safeguards, evidentiary reliability and vendor risk. The legal consequences differ

Executive Summary The September 29 briefing opens with two articles I recently published on Law.com: “7 AI Checks Before Serving a New York Expert Report,” published by the New York Law Journal on September 28, and “When AI Agents Act, Where Should the Human Check Go?,” published by Legaltech News on September 24. The remaining verified developments cover cross-border litigation, evidence, law-firm data security, court access, judicial AI governance, Canadian legal workflows,

Reprinted with permission from the September 22, 2026 edition of the “New York Law Journal” © 2026 ALM Global Properties, LLC. All rights reserved. Further duplication without permission is prohibited, contact 877-256-2472 or asset-and-logo-licensing@alm.com. New York already has the preservation and discovery framework. The practical task is identifying consequential AI records, their custodians and their retention settings early enough to use it. By Pouya Shafabakhsh The ne

Autonomy is not a single switch. This article separates reading, reasoning, drafting, recommending, acting and releasing so authority can expand deliberately. The practical management question is not whether the agent is 'autonomous.' It is which exact permissions are active at each stage, what a person must approve, and what happens when the workflow fails. Why autonomy should be designed as a sequence of gates The outcome: separate capability from authority An agent can be

Agentic automation changes the governance question from 'what did the model say?' to 'what was the system authorized to do?' This article defines the boundaries before development starts. A useful AI agent may retrieve information, call tools, draft, route, update records or recommend actions. That capability is valuable only when the firm can state the operating authority clearly enough for leadership, users and developers to understand the same design. Why agentic readiness

Not every legal AI workload belongs in the same computing environment. This article treats cloud, local and air-gapped deployment as a workflow architecture decision rather than a slogan. The practical question is not which environment sounds safest. It is which environment supports the approved workflow, information boundary, connectivity requirement, provider-access tolerance, evidence need and operating budget. Why environment should follow the workflow The outcome: make d

AI adoption becomes easier to govern when leadership can see where it is actually touching work. Build a practical AI Readiness Map for law-firm workflows, data, ownership and controls.

A final output rarely explains how an AI-assisted decision was produced. This article focuses on proportionate operational evidence so consequential workflows can be reconstructed later. The goal is not indiscriminate logging. It is to preserve enough context about purpose, sources, system state, human decisions, exceptions and change that leadership is not forced to rebuild the story from memory. Why reconstructability matters before a problem occurs. The outcome: know what

How to Decide Whether a Legal Workflow Is Ready for AI The fastest way to waste an AI budget is to automate the wrong work. This article gives leadership a readiness test before the campaign moves into agentic design. The question is not simply whether AI can perform a task. It is whether the workflow is clear enough, bounded enough and measurable enough that automation would improve the operating model rather than preserve confusion. Why 'can AI do it?' is the wrong first qu

Why Legal Workflows Should Be Fixed Before AI Automation Technology should not freeze a broken process into software. This article examines the workflows law firms should simplify, clarify or redesign before adding agents. The goal is not to make every process elegant. It is to remove avoidable friction, define the source of record and make human judgment visible before an automated system begins moving between steps. Why redesign should come before automation Remove Broken S

Why Law-Firm AI Strategy Must Start Before Technology Buying A strategy should help leadership say yes, no and not yet. This article turns AI gap findings into executive decisions about value, priorities, ownership, sensitivity and deployment. Products will change. A useful strategy gives the firm a decision logic that survives those product changes and keeps pilots from competing only on novelty. Why strategy should decide where AI belongs - and where it does not The outcome

A folder full of AI documents can still leave leadership without an operating framework. This article introduces a gap-analysis lens that connects governance artifacts to real workflows. The question is whether policy, ownership, approved use, controls, evidence and change management operate as one system or remain separate good intentions. Why documents do not automatically form a framework The outcome: distinguish governance artifacts from an operating system A firm may hav

How AI Policy Becomes an Operational Legal Workflow AI Policy to Workflow Implementation Workflow? A written AI policy can be thoughtful and still disappear when a real workflow begins. This article moves from principle to operating behavior. The useful question for a Managing Partner, GC, Partner, founder or solo practitioner is not simply whether the firm has AI governance. It is whether the person doing the work can see the control at the point where AI changes a consequen