AI agents, also known as Agentic AI systems, represent the next evolution of enterprise artificial intelligence. Unlike traditional assistants, these systems don't just answer questions; they can execute tasks, coordinate processes, and act autonomously within defined limits.
To operate effectively, these agents need access to reliable, contextualized, and well-governed information, which places document management at the heart of this new technological transformation. Let us explain!
What exactly is Agentic AI?
Agentic AI represents an evolution from traditional artificial intelligence models. While a generative AI-based assistant answers a specific question, an intelligent agent is capable of pursuing a goal, planning actions, and executing them autonomously within an enterprise environment.
For example, when faced with a supplier issue, a traditional system might generate an explanatory report. An intelligent agent, however, could:
• Identify the issue.
• Consult contracts and associated documentation.
• Verify the economic impact.
• Automatically escalate the case.
• Generate communications to the responsible parties involved.
• Record all actions taken.
In other words, it doesn't just analyze; it also acts.
Why AI Agents are Key in Document Management
Most organizations accumulate dozens of documents spread across different systems. When this information is fragmented, duplicated, or outdated, any initiative involving artificial intelligence applied to document management faces significant limitations.
Agents only reason well if they have access to:
1. Human-Generated Content (Intent Layer): Documented policies. "Who can approve a €50,000 expense?" The answer lies in policies, not in SAP.
2. Machine-Generated Data (Operational Nervous System): Logs, telemetry, historical data. "How many times have we approved this vendor?" "What's the average payment time?"
3. Transactional Data (Source of Truth): Purchase orders, invoices, contracts in SAP. The structured data that governs your business.
Without these three categories, the agent makes decisions based on incomplete information.
How AI Agents Will Transform Document Management
For intelligent agents to generate real value, how to recover document downtime, organizations need to build a document foundation ready for automation. This involves working in several areas, as we explain below.
Information Centralization
Agents must be able to locate relevant information regardless of where it is stored. The integration between systems document management systems, ERP, CRM, and corporate repositories is a fundamental requirement to avoid information silos.
Context and Metadata
Information needs to be enriched with metadata that allows content identification. Generating context enables agents to correctly interpret information, so they can act consistently.
Governance and Traceability
Autonomy requires control and a data governance concise one. Therefore, any enterprise AI strategy must incorporate mechanisms that allow auditing actions, managing permissions, applying retention policies, ensuring regulatory compliance, maintaining document traceability, etc.
Without these safeguards, operational risk increases as automation grows.
Practical Example of AI Applied to Document Management
Scenario: An expense approval agent at a company attempts to approve an invoice for €7,500. All transactional data (SAP) indicated it was fine: correct amount, correct price, verified vendor. The agent approved it.
48 hours later: It turns out that vendor had a compliance issue. The agent never knew because that information was in an email 6 months ago, saved in the inbox of a manager who was no longer with the department.
The Solution? Content + process integration. OpenText Extended ECM connected to SAP creates what OpenText calls "Enterprise Information Management" (EIM), a centralized institutional memory.
How does it work?
• Each invoice is automatically linked to its PO, contract, and supporting documents in OpenText.
• Every compliance or risk decision is automatically documented.
• SAP metadata is synchronized in real-time.
• Agents have access to structured Business Workspaces where they see the complete context.
Result: The agent doesn't just see "invoice for €7,500." They see "invoice for €7,500 from vendor XYZ who had a compliance issue 6 months ago, documented here, resolve with operations manager before payment."
Schedule a free diagnostic of AI applied to your SAP system with Brait
Agentic AI represents a significant shift in how organizations automate and execute processes. However, the real challenge lies not solely in the technology, but in the quality of the information that feeds these systems. If your company processes hundreds of invoices a month and your team spends hours reconciling data, or if you have AI pilots that never scaled, contact us!
We will conduct a (no-cost) diagnostic to identify where your company can transition from manual to agentic.
