As organizations shift from testing AI to using it in everyday business, the importance of trustworthy and well-managed information is clearer than ever. Companies are realizing that AI only provides real value when built on secure and governed data. This shift is making document management systems (DMS) more vital, serving as the foundation for accuracy, control, and trust in AI-driven workflows.

The Evolving Role of Document Management Systems

AI can’t work effectively without well-organized content. Leading companies are upgrading their DMS to support secure, scalable AI deployment. These systems help keep sensitive information protected and ensure that data remains reliable and consistent. As organizations adopt AI more widely, the need for a modern, governed DMS becomes even more critical.

Currently, nearly 3,000 organizations are using the iManage Cloud, with around half a million users actively managing documents daily. The company has seen a 28% increase in annual recurring revenue this year, reflecting strong growth in customer adoption and platform usage. This momentum indicates a clear shift toward more secure and governed knowledge management as AI becomes embedded in daily operations.

Governance Challenges and the Need for Control

Research from iManage shows that many companies face governance gaps as they adopt AI. About 25% of employees worldwide are using AI tools without much oversight. Additionally, a third of organizations have already experienced policy violations related to unregulated AI tools. These issues highlight a major risk: without proper governance, AI can lead to scattered knowledge and potential security breaches.

As AI systems scale, these governance gaps can grow worse. Information risk increases when unregulated tools are used across teams. To avoid this, companies are strengthening their DMS to serve as a single trusted source of truth. This helps ensure that AI outputs are based on accurate, authorized data and that information remains secure and compliant with policies.

By focusing on a governed, centralized knowledge system, organizations can maintain control and trust as AI adoption accelerates. This approach prevents knowledge from becoming fragmented across different tools and ensures that AI decisions are grounded in reliable information. The result is a more secure, trustworthy environment for AI-driven insights and automation.

Advancing Governed AI with the Model Context Protocol

As AI becomes more integral to business, companies need platforms that protect sensitive data while allowing AI tools to access information securely. iManage is expanding its Model Context Protocol (MCP), a standard interface that enables approved AI models and agents to securely interact with content stored in their platform.

MCP ensures that AI tools can access information in a way that respects permissions, security policies, and audit requirements. This helps organizations integrate AI safely and responsibly, avoiding data leaks or policy violations. By supporting policy-aligned integration, MCP paves the way for scalable, governed AI adoption across different tools and systems.

This approach allows organizations to embed AI into their workflows without sacrificing control or security. It promotes responsible AI use by ensuring that only authorized models can access sensitive information, all while maintaining oversight and compliance. As a result, businesses can unlock the full potential of AI without exposing themselves to unnecessary risks.

Overall, the move toward trusted, governed AI is transforming how companies manage their knowledge and information. With platforms like iManage leading the way, organizations are building stronger foundations for AI that is both powerful and responsible. This shift is helping businesses operate more efficiently while safeguarding their most valuable data assets.

Inspired by

• https://ai-techpark.com/imanage-momentum-grows-as-organizations-prepare-for-trusted-ai/