Key takeaways from the Gartner report, Evaluating AI for Document Management

As generative and agentic AI move from pilots into daily use, organizations are being forced to confront a practical reality: AI only delivers value when it is grounded in structured, accessible, and well-governed content. 

In the latest research from Gartner, Evaluating AI for Document Management, this idea is explored in depth. We believe the report positions document management as a critical decision point for enterprise AI investments.  

From the report: “Given that only 14% of organizations report high confidence in their content being AI-ready, AI investments in document management have become a strategic imperative for application leaders.”  

To us, this suggests the success of enterprise AI depends increasingly on how documents are being generated and managed across the organization. 

Platform or point solution?

Organizations looking at AI for document management usually face a clear choice. They can invest in one integrated document management platform, or they can piece together several specialized tools for search, extraction, content creation, and automation. 

Specialized tools can work well for specific tasks and often move quickly in narrow areas. The downside is complexity. When tools are spread across systems, integration takes more effort, data is often duplicated, and governance becomes harder to maintain. Over time, this makes it more difficult to control how AI uses and creates enterprise content. 

Document management platforms take a broader view. By bringing content, metadata, and policies together in one place, they create a more consistent and reliable foundation for AI across the entire document lifecycle.  

13 areas where AI impacts document management

In the report, we believe Gartner provides a clear framework for evaluating AI in document management, discussing 13 capability areas that cover the entire document lifecycle. This structure gives enterprises a practical way to assess technology providers, especially in areas like document generation, where not all solutions deliver the same level of control or reliability. 

To us, the key insight is that AI capabilities can vary widely and have deep specialties within the document lifecycle. Document generation, classification, search, and automation each serve different purposes and should be evaluated based on how they support real document workflows.  

Mapping AI capabilities to costs and business outcomes

Cost control is an often overlooked risk area in assessing AI solutions. While the initial cost investment may be straightforward, some solutions can lead to unclear pricing models, unpredictable usage, and long-term contracts that are hard to adjust as needs change. 

To manage this risk, organizations need to choose carefully between specialized point solutions and an integrated document management platform, and understand how each approach affects costs over time. Gartner advises evaluating AI capabilities based on clear business needs and measurable KPIs, rather than adding features without a defined outcome. 

Good cost management also means planning for future usage, expecting price increases, and making sure contracts reflect how AI will actually be used as it scales across the organization. 

Explore the full Gartner report

For a deeper analysis of AI capabilities, cost considerations, and evaluation frameworks for document management, read the full Evaluating AI for Document Management report from Gartner.