Industries GUIDE
The EDRM Model and Where AI Fits
The current EDRM 2.0 model, released September 1, 2026, adds disposition as a core phase, groups identification, preservation, collection, and processing under Data Acquisition, and treats analysis as continuous across the lifecycle.
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Overview
AI can assist within stages; EDRM is a conceptual framework, not a mandatory linear workflow.
Deep Dive
EDRM 2.0 is the current Electronic Discovery Reference Model released by EDRM on September 1, 2026. It places the Information Governance Reference Model as the foundation and groups Identification, Preservation, Collection, and Processing in a Data Acquisition framework. Review remains a focal point, while Production, Presentation, and Disposition describe later handling and use of information.
The model also elevates Analysis from a separate box to a continuous activity that can inform decisions across phases. That shift reflects analytics, machine learning, and generative AI, but EDRM does not add an “AI phase.” A system may help identify sources, process data, prioritize review, analyze relationships, or prepare production; the legal and operational checks remain tied to the work being performed. Disposition addresses systematic retention, deletion, transfer, or return after use, subject to legal holds, retention duties, and agreements.
EDRM is a conceptual reference, not a required sequence or legal rule. Teams may repeat, reorder, or skip phases depending on the matter, and should adapt the framework to jurisdiction, court orders, proportionality, and client obligations. Earlier EDRM diagrams may not include the same groupings or disposition changes, so identify which version a project references. Use the framework to clarify responsibilities and handoffs, then document the actual process and control points. The current definitions also clarify that Review examines relevance, responsiveness, privilege, confidentiality, privacy, and issue significance; Production delivers information in appropriate formats, and Presentation displays it in legal proceedings. These descriptions help teams map automation to real activities.
Strategic Impact
Context and rules
Industry context determines whether AI ideas survive contact with reality.
Quality control
Domain constraints influence acceptable error rates and oversight models.
Build choices
Successful deployments align technical capability with frontline workflows.
The Future of The EDRM Model and Where AI Fits
The new model foregrounds lifecycle governance and continuous analysis as technology changes. AI may appear in more phases, but project teams still need clear scope, human accountability, validation, and records. Future revisions may adjust the framework, so use EDRM’s current model and state which version informs a plan. Organizations may update workflows as AI changes, but version-specific documentation and governance stay important. EDRM can help explain where work occurs; it does not define a universal AI control or replace agreements, local rules, or judicial orders.
Real-World Implementation
A legal team maps preservation, collection, review, analysis, and disposition responsibilities.
A project manager uses EDRM 2.0 to discuss data acquisition and review handoffs.
Counsel documents where AI-assisted classification supports discovery decisions.
An organization plans defensible deletion or transfer after a matter concludes.
Risks & Guardrails
Regulatory requirements can invalidate otherwise strong prototypes.
Historical data may encode bias that harms specific communities.
Legacy systems can create integration bottlenecks and hidden costs.
Implementation Roadmap
Involve domain experts from problem framing to evaluation.
Design audit trails and documentation before launch.
Validate compliance and safety obligations early.
Roll out in phases with clear stop and rollback criteria.
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Frequently asked questions
What is The EDRM Model and Where AI Fits?
The current EDRM 2.0 model, released September 1, 2026, adds disposition as a core phase, groups identification, preservation, collection, and processing under Data Acquisition, and treats analysis as continuous across the lifecycle. AI can assist within stages; EDRM is a conceptual framework, not a mandatory linear workflow.
Which change appears in the current EDRM 2.0 model released in 2026?
EDRM 2.0 adds disposition and elevates analysis across phases.
Which EDRM 2.0 activities are grouped in the Data Acquisition framework?
The current model groups those four early-stage acquisition activities.
What does EDRM say about the order of its stages?
EDRM describes a flexible reference framework, not a literal waterfall.
Under EDRM 2.0, where can AI tools support work?
EDRM 2.0 treats analysis as continuous and AI can support existing activities; the framework does not add a separate AI phase or replace accountability.
After production or presentation, which task does EDRM 2.0 call disposition?
The current model adds post-use data management as a core phase.
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