Most law firms already hold their most valuable knowledge inside their document management system (DMS). For many, that system is iManage or NetDocuments. Precedents, playbooks, checklists, clause banks, client guidance, and approved templates all sit inside the DMS.
The real strategic question is not where knowledge lives. It is whether your firm can consistently find, trust, reuse, and scale that knowledge for AI and firm collaboration.
If lawyers still ask colleagues before searching the system, if knowledge is duplicated, or if AI pilots feel risky because of content inconsistency, then your iManage knowledge is not yet fully unlocked.
This article explores three strategic approaches:
Why DMS based knowledge is both an asset and a constraint
The DMS is often the most governed system in the firm. It has security, ethical walls, auditability, and strong document version control. It is also where lawyers naturally store work product. That makes it a logical place to anchor KM. The problem is that a DMS is optimized for document management, not necessarily for knowledge reuse at scale.
However, as the iManage Knowledge Work Maturity Model highlights, advancing knowledge maturity requires alignment across people, process, technology, and culture. A DMS alone does not automatically deliver reusable, contextualized, AI-ready knowledge.
Managing knowledge entirely within your DMS, such as iManage or NetDocuments, is a rational and often conservative strategy. It builds on existing infrastructure, leverages established governance controls and avoids introducing another platform into an already complex technology landscape.
Firms adopting this approach position the DMS as both the authoritative system of record for KM content and the primary user experience for finding, validating, and reusing that knowledge, effectively relying on the document management platform to serve as the foundation for knowledge lifecycle management.
This approach works best where:
Pros
Cons
Managing KM within your DMS is a defensible and often necessary starting point. It strengthens governance and centralizes control. The strategic question for leadership is whether that foundation alone is sufficient to support the firm’s ambitions around productivity, cross-practice collaboration, and AI enabled knowledge discovery at scale.
This approach does not replace iManage. Instead, it introduces structure by separating reusable knowledge from matter content.
Client work remains in iManage as the secure system of record. However, curated KM content is copied or promoted into a dedicated iManage workspace designed specifically for reusable knowhow. Atlas then layers automated tagging, contextualization, and enhanced search on top of that curated environment.
In architectural terms, iManage manages documents. The knowledge layer manages meaning, context, authority, and discoverability.
What this means in practice:
This reflects the broader shift from traditional knowledge management to knowledge productivity, where knowledge is contextual, automated, and embedded into daily workflows rather than accessed as a static library.
Pros
Automated tagging and enrichment shift the KM team away from repetitive classification tasks and towards governance and quality oversight.
Knowledge appears within the flow of work inside Microsoft 365 and Teams, reducing friction and improving adoption.
Structured foundation for AI grounded in curated KM collections.
Cons
Content rationalization needed: Legacy duplication and outdated materials must be addressed to avoid amplifying noise through improved search and AI surfacing.
Requires governance clarity: Authority, ownership, lifecycle standards, and review cadence must be clearly defined before scaling visibility.
This approach works best where:
In summary, introducing a structured knowledge layer around iManage is an incremental maturity step. It retains iManage as the authoritative store while introducing structure and automation through Atlas.
This approach makes a deliberate distinction between document management and knowledge management.
It is the most strategic model, with iManage remaining the system of record for client and matter documents. Reusable KM content is migrated into Atlas as the primary knowledge layer, which then acts as the authoritative environment for precedents, playbooks, guidance, and curated expertise. Knowledge is structured, contextualized, and delivered directly within Microsoft 365 workflows.
This represents a shift from thinking in terms of repositories to thinking in terms of knowledge infrastructure.
What this looks like in practice:
This aligns directly with knowledge productivity principles, where contextual, automated, and workflow-embedded knowledge replaces static libraries
Pros
Cons
Requires rationalization of knowledge content.
Cultural change required whereby lawyers must understand that reusable knowledge no longer “lives” in matter folders.
This approach works best where:
Approach 3 represents a strategic shift. It treats knowledge as core enterprise infrastructure rather than a curated subset of documents. Client work remains securely governed in iManage, while reusable knowledge is moved into Atlas, where it is structured, enriched, contextualized, and made AI‑ready.
For firms serious about AI at scale, cross-border collaboration, and measurable knowledge ROI, this model provides the cleanest long-term architecture.
Final perspective: from iManage repository to knowledge layer
Moving from a DMS-centric model to a knowledge layer is an operating model change. The aim is not to move everything out of iManage, but to identify and elevate reusable, high-value know-how so it is easier to find, trust, reuse, and use safely with AI.
Successful firms keep iManage as the secure system of record and add a knowledge layer to operationalize a defined subset of KM content. This preserves governance, avoids duplicating controls, and focuses effort where it delivers measurable impact.
The shift from DMS-centric KM to a knowledge layer is about extracting more value. By retaining iManage as the system of record and operationalizing knowledge through a structured layer, firms improve findability, increase reuse, reduce manual KM effort, and enable safer AI adoption. This is the difference between knowledge being stored and knowledge being usable.
Should we move everything out of iManage?
No. For most firms, iManage should remain the secure system of record for documents, communications, and compliance controls. A knowledge layer is not designed to replicate your entire DMS. It is designed to surface curated, authoritative KM subsets that are intended for reuse.
Moving everything increases noise, governance complexity, and risk. The strategic objective is not migration. It is operationalization of reusable knowledge.
No. Atlas is best understood as an enhancement to iManage rather than an alternative to it.
iManage continues to manage documents, version control, and compliance. Atlas structures, enriches, and surfaces curated knowhow so it becomes easier to find, validate, and reuse in context. The two serve complementary roles in modern legal KM architecture.
Will automated tagging remove the need for KM teams?
No. Automation reduces manual classification effort, particularly around metadata and tagging. However, governance, authority definition, lifecycle discipline, and quality control remain essential.
In fact, as automation increases, governance becomes even more important.