Litigation AI GRC Briefings & Analysis for Law Firms

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

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

Why 90 days is a useful planning horizon The outcome: move from AI discussion to one controlled implementation cycle A law firm does not need to solve every AI governance question before making progress. It needs a sequence that is short enough to create momentum and disciplined enough to prevent a pilot from becoming an uncontrolled dependency. A 90-day roadmap can do that if it is treated as a planning model rather than a guaranteed schedule. The first 30 days create visibi

The campaign now moves from individual controls to system architecture. This article connects seven layers into one law-firm AI operating model that can be reused across future workflows. The aim is not to force every firm into an identical framework. It is to make the dependencies visible enough that leadership can see what changes when a new workflow, agent, vendor or environment is introduced. Why one operating model matters more than many isolated policies The outcome: a