The rise in generative AI has prompted many organizations to adopt or upgrade their document management systems.
AI-powered document management systems (DMSes) can analyze documents, extract relevant information and map it to other enterprise tools. They can also reduce manual efforts as they augment or automate document creation and customization. However, these tools can also raise concerns about AI hallucinations and accuracy, so they require additional oversight.
To choose the right DMS, content managers should evaluate many tools to make sure they meet their organizations' needs. Key features of an effective DMS include cloud access, multisource document input, version control, provenance tracking and security.
14 features to look for in a document management system
Modern DMSes offer capabilities beyond document storage, such as workflow automation and e-signature tools. To choose the right system, content managers should consider the following features.
1. Cloud access and permissions
Organizations with remote or hybrid workers rely on cloud access because it lets users work on documents from any device. Additionally, it can prevent data loss and offers permissions that restrict access to workers who need it.
Cloud-based systems also improve integration with generative AI (GenAI) workflows because they offer APIs that can easily connect AI tools to data. Yet, this requires additional focus on permission management to prevent unauthorized AI access to sensitive data.
2. Multisource document input
A DMS should support various input methods, such as email, scanners, apps and bulk uploads, to improve efficiency and reduce manual work. Organizations should also evaluate how well these inputs integrate with current workflows to ensure smooth operations. For example, a DMS that connects with financial software could automatically trigger a payment process as users upload invoices.
3. Version control
Document version control features can help teams coordinate changes as they communicate about complex products, particularly in manufacturing, said Maximilian zur Muehlen, business strategy manager at VEM Tooling Group, an injection molding company in China.
For example, in product development, engineers frequently update bills of material while procurement teams adjust purchase requests. Version control tracks these changes to help employees find the most current information. These features have helped zur Muehlen's team identify and avoid communication issues that arise when employees work with outdated documents.
4. Provenance tracking
GenAI tools can automate document updates and creation. Yet, they also make different kinds of mistakes than humans, so they require additional version control and audit trails.
For example, humans might misspell names or quantities, whereas GenAI can hallucinate content that sounds authoritative but lacks alignment with enterprise policies or terms and conditions. A DMS should make it easy to surface this content so a human can approve it.
5. Security
A DMS should include in-transit and at-rest encryption, support for role-based access, comprehensive audit trails and revision indexing abilities to protect sensitive data. These features improve security and simplify compliance.
Increasingly, zero-trust security features help enterprises implement more fine-grained access controls to protect against modern cyberattacks. The DMS should also support industry-specific or geographical security requirements, such as HIPAA compliance in healthcare or GDPR in the EU.
6. Intelligent search
As users add documents to a database, categorization becomes more challenging, and employees might struggle to find documents. Therefore, content managers should pay close attention to a DMS's categorization capabilities, such as tagging and rating, because they can help users locate files.
Additionally, some GenAI features can distill information into more categories and improve search even when documents use different spellings or terms for the same entity or concept.
Understanding the document management process can help content managers find the right DMS.
7. Advanced indexing
Content managers should research the tools' advanced document indexing capabilities -- which categorize and structure documents -- to improve document organization and retrieval. Proper document indexing ensures users can quickly find relevant files, enforce access controls and create reports based on document usage and access patterns.
Some of the most popular document indexing features include the following:
Metadata indexing.
Content recognition and indexing.
Version and revision indexing.
Automatic document numbering.
8. Pull printing
Tightly regulated firms may want to consider pull printing support, which prevents documents from printing until users authenticate themselves at the device, said Bob Burnett, director of B2B solutions deployment and planning for Brother International Corporation. This capability protects documents from unauthorized personnel and can prevent crowding around the printer.
9. Hyperautomation
Robotic process automation can automate document workflows, but users must manually create the RPA bots. Hyperautomation, on the other hand, can automate the process of creating automation.
Some hyperautomation features have human-in-the-loop capabilities, which let the system learn and improve based on human input. This technology can also accelerate integrations with AI, RPA and cloud initiatives, said Sam Bobley, CEO and co-founder of Ocrolus, a financial document automation platform.
10. App marketplaces
DMS vendors have begun to create app marketplaces that offer third-party tools and workflows, such as apps to process industry-specific documents. These apps can manage information more efficiently than external tools like RPA.
For example, intelligent document processing (IDP) apps can accurately extract data from invoices, even if layouts vary between suppliers. Industry-specific apps also offer prebuilt workflows tailored to specific sectors, including fraud detection for finance teams and claims processing for insurance agents.
11. Enterprise software integration
To streamline workflows, a DMS should easily connect to enterprise applications the organization already uses, such as CRM, ERP and finance tools. However, integration capabilities can vary in complexity.
For example, basic integrations might let users send or consume documents as a unit with the other apps. More sophisticated integrations might automatically map document information to the other apps to improve customer data analysis, streamline processes and improve scalability.
12. E-signatures and digital signatures
The ideal DMS includes a workflow to streamline existing approval processes within a company or agreements with customers and suppliers, captures e-signatures, ensures legal verification and enables audits. It should also let customers sign documents with a weblink and possibly their mobile devices to speed up the signature process.
13. Contract lifecycle management
Organizations in contract-heavy industries, such as finance and legal, may require contract lifecycle management capabilities that use AI to automate contract creation, reuse and analysis. Some DMS vendors include these features natively in their offerings, and others offer them in an app marketplace or through integration with a separate tool.
14. Blockchain
A few smaller DMS vendors have experimented with blockchain technology to offer a decentralized ledger, which can improve visibility and accountability across multiple parties. For example, in real estate transactions, blockchain can verify property titles and ensure all parties access up-to-date records, without the need for a central authority.
However, these tools add additional complexity. Content managers should carefully evaluate if and how blockchain technology could add value to their particular use case, especially as major DMS vendors have yet to adopt standardized frameworks for blockchain-based document management.
A DMS helps teams move beyond the limits of paper-based workflows and brings all their business systems online.
What is a document management system?
A DMS helps teams move beyond paper-based workflows and bring all their systems online. It also offers a more structured alternative to simple file management systems, as it improves security, document sharing and collaboration across workflows and applications.
Why does an organization need a document management system?
Every organization has its own requirements. Smaller businesses might appreciate the opportunity to digitize manual and physical processes. Larger firms may want advanced capabilities to integrate document data across various customer, financial, legal and compliance workflows more efficiently and with more granularity. These sophisticated capabilities are becoming more accessible and cost-effective because of improvements in AI, RPA and the cloud.
A DMS implementation can automate certain processes and improve complex workflows for various types of documents. It can eliminate human error, improve access to content and reduce the time employees spend searching for documents. Organizations with a high volume of documents will likely see the most significant gains from deploying a DMS.
Technology driving document management system adoption
IDP is an emerging capability that can automate DMS capabilities. It applies optical character recognition to identify text, AI to interpret the text's layout and meaning, and RPA to automate workflows within a DMS.
Additionally, cloud technology offers sophisticated APIs to improve data exchange between DMSes and other applications. Combining IDP and cloud can help organizations build more sophisticated AI and machine learning models. For example, financial companies can use IDP-powered DMSes to automatically extract more granular data from bank statements, pay stubs and tax documents. This lets organizations create more accurate models to predict credit risks, identify fraud and improve planning, Bobley said.
Additionally, more advanced GenAI capabilities can extract entities, terms, items and other data types from documents and improve other processes in conjunction with IDP. Organizations can also connect this more refined data to various applications to improve customer and employee experiences.
However, GenAI is prone to hallucination. Therefore, to build trust with employees, regulators and customers, enterprises need systems to flag generated content for human approval.
Editor's note:This article was written in 2021. It was updated and expanded in 2025.
George Lawton is a journalist based in London. Over the last 30 years, he has written more than 3,000 stories about computers, communications, knowledge management, business, health and other areas that interest him.
