Eighty-five per cent of organisations are piloting or implementing artificial intelligence. Only 17% have actually integrated it.
That gap—68 percentage points of aspiration meeting infrastructure reality—is reshaping how legal and professional services firms choose their core systems. And iManage just reported the numbers to prove it.
The knowledge management platform added 340 new clients in 2025, pushing its cloud adoption to 71% of its global customer base. More tellingly: 83% of the Top Global 100 firms now run on iManage, alongside 40% of the Fortune 100 and 79% of the AM Law 100. For a sector that moves cautiously on technology decisions, the velocity matters.
The shift reflects something deeper than feature preference. Firms aren’t just buying document management anymore—they’re buying the infrastructure layer that determines whether their AI investments will function at scale or collapse under real-world demands. The iManage Knowledge Work Benchmark Report 2026 surfaced the 85%-versus-17% execution gap, and it’s become a market-defining statistic. AI workloads require centralised, governed content environments. Without that foundation, the chatbots and semantic search tools remain demos, not systems of record.
iManage Cloud delivered 99.98% uptime in 2025. Over the trailing 12 months, that figure climbed to 99.99%, with sub-second response times across global deployments.
Those aren’t flashy numbers, but they’re the ones that matter when a Magic Circle firm’s entire document repository needs to respond to natural-language queries at 9am on a Monday. Reliability became the quiet differentiator—less about innovation theatre, more about whether the system stays live when 5,000 lawyers hit it simultaneously.
Neil Araujo, iManage’s chief executive, framed the market dynamic bluntly. “Organisations recognise that successful AI adoption depends on a trusted knowledge foundation that is not only secure and governed, but consistently reliable,” he said. “By centralising institutional knowledge, embedding governance at every stage of a document’s lifecycle – from creation to archiving – and delivering the stability law firms expect from a system of record, iManage provides the foundation organisations need to put AI to work in their everyday workflows, while preserving governance, stability, and the assurance that the right information reaches the right people.”
The pitch is infrastructure-first. AI capabilities come second.
At the centre of iManage’s AI strategy sits Ask iManage, a natural-language search layer embedded directly within iManage Work. Users pose questions across documents, matters, emails, and institutional knowledge; the system returns contextual, cited answers drawn from governed content. Each response links back to source materials, enabling verification. The design activates knowledge in place rather than forcing bulk exports or creating fragmented repositories outside the core system.
By embedding AI-powered search within the document management system itself, iManage transforms the DMS from passive storage into an active knowledge layer. The distinction matters: firms don’t need to migrate content to external AI tools, which introduces governance headaches and version-control chaos.
But organisations also want to connect governed knowledge to external AI environments they’ve already invested in—tools like Harvey, Legora, and Microsoft Copilot. To address that, iManage is extending platform openness through support for the Model Context Protocol. MCP allows secure connections between iManage’s governed knowledge base and external AI tools without requiring bulk exports or custom integrations. Governance controls remain intact even as users access iManage content from approved AI environments.
iManage MCP is targeted for general availability in the first half of 2026.
The Model Context Protocol represents a pragmatic acknowledgment: firms will adopt multiple AI tools, and the knowledge platform needs to feed them all without fragmenting the system of record. Rather than competing directly with specialised AI applications, iManage is positioning itself as the governed data layer underneath—the infrastructure that makes those tools trustworthy.
Governance itself has shifted from compliance checkbox to competitive advantage. As work increasingly happens across collaboration tools—Microsoft Teams, SharePoint, third-party platforms—organisations face a choice: support productivity or maintain control. iManage’s answer involves native co-authoring, deep Microsoft 365 integrations, secure Collaboration Links, and Bundle Builder, which lets professionals compile client-ready deliverables in minutes without creating uncontrolled copies in external systems.
The approach meets users where they work while keeping iManage as the system of record. Productivity without chaos.
iManage Disposition Manager, launched recently, applies policy-driven retention and enables defensible disposition across knowledge environments. Adoption has been rapid, particularly among firms navigating regulatory requirements and compliance risk. The capability reinforces the governance layer that AI systems depend on—ensuring the knowledge foundation remains accurate, current, and legally defensible.
The market responded. At Legalweek 2026 in New York earlier this month, iManage received the Innovating Knowledge Management award in the Legalweek Leaders in Tech Law Awards. The recognition came as the company showcased its AI and governance capabilities at booth 116, while simultaneously presenting at the British Legal Technology Forum in London on 10 March.
At BLTF, iManage hosted a 15-minute Innovation Stage session titled “The Intelligent Nervous System: How MCP and Semantic Search are Rewiring the Modern Firm,” featuring Saran Kaur, a legal operations change and transformation professional, and Jan Van Hoecke, iManage’s vice-president of data science. The session examined how MCP, semantic search, and Ask iManage are transforming the DMS into an intelligent, connected knowledge layer for AI-driven legal work.
The timing of the dual-continent presence underscores the global expansion iManage is pursuing. With more than one million professionals at 4,000 organisations relying on the platform—and cloud adoption now exceeding 70%—the company is banking on a market thesis: that AI readiness depends less on bleeding-edge algorithms and more on the boring, essential work of centralised knowledge management and rock-solid uptime.
Whether that thesis holds depends partly on how quickly competitors respond and partly on how fast the 68% of organisations stuck in AI pilot purgatory decide infrastructure matters more than features. For now, the 340 new logos suggest the message is landing.
The H1 2026 timeline for MCP will test whether iManage can maintain momentum as external AI tools mature and firms demand tighter integrations. The answer will likely determine whether the current growth trajectory represents a temporary flight to reliability or a longer-term realignment of how professional services firms architect their knowledge systems.
What’s clear: the gap between AI ambition and AI execution isn’t closing through better algorithms alone. It’s closing through the infrastructure layer most firms didn’t realise they needed to rebuild.
