Enterprise Agent Architecture™
A practical framework by DISRUKTECH Research for AI agents that use business context, reason over enterprise knowledge, act through real tools and stay under accountable human and operational control.
The framework in five sentences.
- 01
An enterprise agent is defined by accountable action, not by conversation.
- 02
It connects business context, enterprise knowledge, reasoning and tools to act in real systems.
- 03
Governance and human oversight run across every layer; they are not a final approval step.
- 04
Autonomy is a design variable: it grows only where the organization can observe, limit and reverse the agent.
- 05
As authority increases, control must become more explicit.
From intelligence, to assistance, to execution.
Intelligence
Systems that produce information.
Assistance
Systems that support decisions.
Execution
Systems that take bounded actions.
The challenge is not only model capability. It is designing context, knowledge, reasoning, tools, permissions, governance and oversight as one operating system.
Six layers. Governance and oversight across all of them.
01 · Business Context
What the agent is trying to achieve, for whom, and inside which business process.
- Which process and outcome does the agent serve?
- Whose role and authority does it act under?
02 · Enterprise Knowledge
The transactional data and the documents the agent may use, with the same access rules people have.
- Which data and documents are allowed for this task?
- Can each answer be traced to its source?
03 · Intelligence & Reasoning
How the agent breaks the goal into steps, evaluates options and decides what to do next.
- Are the steps and the decision explainable?
- How is quality tested before and after launch?
04 · Tools & Actions
The specific actions the agent can take, each through an authenticated, limited interface.
- Which actions are allowed, and up to what limit?
- Can every action be reversed?
05 · Enterprise Systems
The systems of record where the action lands, integrated without weakening their controls.
- Does the agent use supported interfaces?
- Are the system's own controls still enforced?
06 · Business Outcomes
The result the business measures: cycle time, errors, cost or risk.
- Which metric should move, and by how much?
- Who owns the result after launch?
As authority increases, control must become more explicit.
Autonomy is a design variable. It expands only where the organization can observe, constrain and reverse the agent.
Analyze
The agent reads data and explains what happened. It changes nothing.
- Read-only access
- Sources cited in every answer
- Decides and acts
Recommend
The agent prepares an action with its evidence and waits for approval.
- Policy check before each recommendation
- Approval queue with explanation
- Approves or rejects
Execute within policy
The agent acts on its own, only inside limits the business has defined.
- Thresholds and segregation of duties
- Audit log, reversal path and stop switch
- Reviews exceptions and samples
Requirements, not decorative governance.
Agent identity
Its own identity, never a person's credentials.
Least privilege
Only the access the task needs.
Segregation of duties
The same rules that apply to people.
Approval thresholds
Amounts and cases that always need a person.
Observability
Inputs, decisions and actions logged.
Reversal
Every action can be undone or stopped.
Vendor invoice exception, through the layers.
- Context
An invoice is blocked
Price variance against the purchase order.
- Knowledge
Gather evidence
PO, goods receipt, contract and history.
- Reasoning
Explain the cause
Approved amendment, or a real discrepancy.
- Action + control
Act or escalate
Release within threshold; otherwise route to a person.
- Typical timing; the final plan depends on scope.
- EVENT
Invoice INV-20481 blocked · price variance 4.2%
- CONTEXT
PO 4500-1187 · goods receipt posted · price amendment on file
- REASON
Variance matches the approved price amendment
- GATE
Auto-release ≤ 5% and ≤ $10,000 · SoD ok · PASS
- ACTION
Payment block released in SAP S/4HANA
- AUDIT
Inputs, rule, decision and reversal path logged
- Layer-by-layer design of one agent
- Autonomy level and control set
- Reference architecture for your systems
How to cite this framework.
Espinosa, A. (2026). Enterprise Agent Architecture™ (Version 1.0). DISRUKTECH Research. https://disruktech.com/research/enterprise-agent-architecture
- AuthorArturo Espinosa
- PublisherDISRUKTECH Research
- Version1.0 · 9 Oct 2026
- ReviewPractitioner publication; not peer reviewed
Questions to resolve before starting
What is an enterprise agent?+
An AI system that combines business context, enterprise knowledge, reasoning and tools to pursue an outcome inside explicit authorization, control and human-oversight boundaries.
How is it different from a chatbot or copilot?+
A chatbot answers; an enterprise agent can act in business systems. That is why identity, permissions, audit and reversal become part of the architecture.
What are the layers of Enterprise Agent Architecture™?+
Business Context, Enterprise Knowledge, Intelligence & Reasoning, Tools & Actions, Enterprise Systems and Business Outcomes, with Governance and Human Oversight across all of them.
How does it apply to SAP and Joule?+
The same layers apply whether the agent is SAP's own (Joule), extended with Joule Studio or BTP, or custom-built. The framework helps decide where each fits and which controls it needs.
Is this framework peer reviewed?+
No. It is a practitioner framework published by DISRUKTECH Research as a web edition.
Apply the framework to one real process.
We'll design the agent layer by layer, with the controls it needs.