From Static Repositories to Agent-Ready Platforms
Document management systems are evolving from passive repositories that store files into active platforms that orchestrate knowledge, govern access, and coordinate AI agents across complex enterprise workflows. At ConnectLive, iManage’s leadership framed this shift as comparable in scale to the industry’s move to cloud, arguing that the DMS now needs to act as the core intelligence and control layer for AI in knowledge-heavy organisations. Instead of only indexing and securing documents, the platform is being redesigned to surface relevant work product, understand matter context, and broker governed access for AI tools. This repositioning means document management systems will no longer sit quietly in the background: they are being placed at the centre of AI strategy, where questions of permissioning, audit, and ethical walls converge with the promise of agentic workflow automation.
Inside iManage’s Agentic Pivot at ConnectLive
At the Chicago leg of ConnectLive, iManage detailed a “context fabric” sitting above firm data, designed to give AI agents permission-aware access to matters, documents, and institutional knowledge. The company paired this with new AI-specific controls, expanded monitoring of agent activity, and enhancements to its MCP Server, signalling a platform rather than a feature refresh. According to Legal IT Insider, iManage claims adoption in 79% of the Am Law 100 and 83% of a defined “Top Global 100,” which means this repositioning will influence how a large share of major firms structure their AI stacks. This is not a niche experiment: session tracks such as “AI and the Agentic Journey” focused on turning the DMS into the governance layer through which any connected AI system must pass, putting document management systems at the centre of both opportunity and risk.
Agentic Workflow Automation: What Changes for Enterprise Teams
The move toward AI agents in enterprise document management systems reshapes everyday work. Instead of users pulling documents from a static repository, agentic workflow automation means AI agents can act on behalf of teams: surfacing prior work product, drafting summaries based on governed access, or routing documents according to ethical walls and client rules. iManage’s roadmap highlights capabilities like ethical-wall-aware agents and granular client- and matter-level AI restrictions, which turn the DMS into an active decision engine embedded in legal, compliance, or knowledge processes. For enterprise teams, that implies fewer manual handoffs and more autonomous execution of repeatable tasks, but also a need for clear audit trails and oversight when agents act across multiple systems. The DMS platform evolution is about more than productivity; it is about ensuring that every AI action is tied back to policy, permissions, and traceable context.
The New Governance Battleground in the AI Stack
ConnectLive’s discussions showed that agentic AI is opening a governance contest around where control should sit. iManage’s context fabric argues that the DMS should serve as the primary control plane, brokering access between any AI tool and the firm’s corpus of documents. Competing moves from NetDocuments, Aderant, and legal AI platforms signal that several vendors now aim to own this governed surface. For CIOs and knowledge leaders, the question is whether governance lives in the DMS, in a separate orchestration platform, or in practice management. Attendees, skewing toward infrastructure, security, and knowledge management roles, focused less on AI feature checklists and more on threading AI agents through existing records, security, and ethical-wall regimes. Document management systems are no longer peripheral utilities; in the era of AI agents enterprise strategy, they are becoming the political and technical centre of the stack.