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The following Utility Voice was authored by Marc Rosson, Community Connector at Utility.Community. For more SAP utilities insights, sign up to receive ASUG’s free The Topic: Utilities newsletter, and to get involved and keep up with the latest, join ASUG’s Utilities Community. Connect with SAP teams across the utilities community as they explore AI adoption, clean core, data strategy, and more at SAP for Utilities, Presented by ASUG in San Antonio, October 6 – 9, 2026.
Last month in this space, I argued that SAP’s Autonomous Enterprise vision is the right move for utilities precisely because it puts governance, security, and performance at the foundation rather than treating them as afterthoughts. The response from our community was encouraging and predictable. The most common follow-up question, in one form or another, was this:
“That all sounds good. But who actually secures an enterprise where software agents are doing the work?”
It is exactly the right question, and it belongs squarely in the category I’ve been calling the questions we aren’t asking. We have decades of muscle memory for securing systems that humans operate: role-based access, segregation of duties, change management boards, audit logs tied to a user ID and a badge number. Every one of those controls assumes a person on the other end of the transaction.
An autonomous enterprise breaks that assumption. When an agent closes a work order, adjusts a billing account, or recommends a switching plan, our security model has to answer questions it was never designed for: Who authorized this agent to exist? What rules govern what it should be doing? Who is watching what it actually does? Where does it sit in the organization? And if it misbehaves, how do we shut it down?
The good news is that SAP’s answer to these questions is taking shape, and it is more complete than most of our community realizes. It comes in three layers: a hardened operational foundation that exists today, a published security operations pattern that connects SAP detection into your enterprise SOC, and an emerging agent governance stack that addresses the questions above directly.
Layer One: The Foundation Most of Us Already Have
Before we talk about securing agents, we should be honest about something: many of the security capabilities utilities will need for the autonomous era are already part of the RISE with SAP operating model, and many of us have never looked closely at them.
RISE is built on a shared security responsibility model. SAP Enterprise Cloud Services (ECS) takes end-to-end responsibility for the platform layer: hardened systems and isolated landscapes, managed backup and restore, HANA database management, threat and patch management, 24×7 security monitoring, and incident response through SAP’s global security operations. The hyperscaler (AWS, Azure, or Google Cloud) secures the physical and virtual infrastructure beneath it. The customer retains responsibility for what has always been ours: application user identity and access, roles and authorizations, business process configuration, data ownership, and compliance with the regulations that govern our industry.
That model is governed against a familiar frame for utility security teams: the NIST Cybersecurity Framework, with its Identify, Protect, Detect, Respond, and Recover functions, backed by the certification and attestation portfolio (ISO 27001 family, SOC 1, SOC 2, and others) that our compliance teams already know how to consume.
Two ECS services deserve particular attention from utilities planning for agentic AI, because they answer the visibility question: how do we see what is happening inside a managed environment?
LogServ is ECS’s log collection and retention service. It centralizes logs from the systems, applications, and ECS services in your landscape, supports near-real-time integration into your own SIEM, and offers configurable retention by data source, from one month up to 10 years. For utilities, that retention range matters: NERC CIP evidence requirements, rate case discovery, and incident forensics all demand log histories far longer than default system retention provides.
RAVEN extends that visibility to the SAP application layer itself, historically the blind spot in most utility SIEM deployments. RAVEN delivers SAP application security and threat reporting, security use cases as a service, and user behavior analytics, all feeding into the customer’s own SIEM. Your security operations center finally gets to see SAP application threat activity in the same pane of glass as the rest of the enterprise.
Why does this foundation matter for the autonomous enterprise? Because agents will run on these systems. An agent’s actions will generate application logs, security events, and behavioral patterns. If your organization has not already wired this telemetry into your security operations, you are not ready to monitor humans in your SAP landscape, let alone agents. That telemetry work is homework we can begin today.
Layer Two: The Security Operations Pattern Is Already Published
What much of our community has missed is that SAP’s Architecture Center has already published a reference architecture for exactly this integration: Log-Driven Security Operations with SAP Enterprise Threat Detection and SIEM/SOAR Platforms. Contributed by SAP partner Fortinet, it documents the end-to-end pattern, and it deserves a place on every utility security architect’s reading list.
The flow will feel familiar to anyone who has built a security operations program. SAP systems across the landscape (RISE workloads, BTP applications, SaaS solutions, and on-premises systems) emit security-relevant telemetry: authentication activity, authorization changes, administrative actions, and application access traces. SAP Enterprise Threat Detection (ETD) applies SAP domain-aware parsing and detection logic to identify suspicious activity, the deep SAP context that generic SIEM tooling has never parsed well. Those findings flow into the enterprise SIEM, where they are correlated with identity, endpoint, network, and cloud signals to surface cross-domain attack scenarios that no single system can see alone. A SOAR platform then orchestrates the response: enrichment, evidence collection, ticket creation, approval workflows, and SAP-aware containment actions such as terminating user sessions, locking accounts, and changing authorizations. Outcomes feed back into detection logic, closing the loop.
Two characteristics of this architecture matter enormously for utilities. First, it formalizes a separation of operational responsibilities that mirrors how most utilities actually staff these functions: SAP security and Basis teams operate ETD, while the enterprise SOC operates the SIEM and SOAR. Second, its response actions are governed: automated playbooks with approval steps, full documentation of every action and decision, and synchronization with ITSM. That is auditability by design, which is the only kind our regulators will accept.
Now connect this to the agent question. That closed loop of detect, correlate, respond, contain, document, and improve is the operational pattern in which agent security will live. When an agent misbehaves, “respond” looks like the same SAP-aware actions the architecture already documents: terminate the session, lock the identity, revoke the authorization. The kill switch for an AI agent is an identity-and-access action, which means it already has a home in this architecture. What’s missing is not the pattern; it’s the agent-specific detection content and the guarantee that agent actions are distinguishable from human actions in every log stream. More on that below.
Layer Three: Governing the Agents Themselves
A hardened platform secures the building, and the security operations pattern determines who watches it and how they respond. Neither one defines what the new digital workforce inside is allowed to do. That is the job of the agent governance stack SAP is now assembling, and it starts with a blueprint that, again, is already published.
The Blueprint: A Published Agent Architecture
SAP’s Architecture Center reference architecture for Agentic AI & AI Agents lays out how agents are built, connected, and trusted in the SAP ecosystem. Joule sits at the center as the orchestrator. Custom agents run on BTP through two paths: low-code agents built in Joule Studio, which register automatically with Joule and run on a managed runtime, and pro-code agents built with the SAP Cloud SDK for AI using frameworks like LangGraph and CrewAI, connected through the open Agent2Agent (A2A) protocol. Tool and data connectivity flows through an MCP Gateway in SAP Integration Suite. And threading through every connection in the diagram is one component utility security architects should study closely: SAP Cloud Identity Services manages authentication, authorization, and identity federation across all of it. Trust in this architecture is brokered at every connection, never assumed.
The architecture also embeds guardrails at the model layer through the Generative AI Hub: grounding, data masking, and input/output filtering, which is where controls like “customer data never leaves defined boundaries” get technically enforced rather than merely documented.
For security teams, the practical significance is this: when your CISO asks how an agent gets into your landscape, what it can touch, and who vouches for its identity, the answer now starts from a published, downloadable solution diagram rather than a whiteboard sketch, which gives architecture review an actual artifact to work from. That is how every other critical system in a utility gets governed, and agents should be no different.
One more point with direct bearing on last month’s lock-in discussion: the architecture explicitly embraces open standards, with A2A as the preferred protocol for multi-agent collaboration and MCP for tool connectivity, and is designed so that third-party platforms like Google Vertex AI, Microsoft Copilot Studio, and AWS Bedrock can delegate tasks to Joule agents and vice versa, leaving the integration layer open. As I argued in May, the proprietary value accumulates in the memory and context layer, which is precisely why that layer needs the strongest governance.
Design: Process Atoms
SAP’s process atom concept decomposes business processes into small, well-defined, reusable units of work, each with explicit inputs, outputs, and boundaries. For security purposes, this is more important than it sounds. You cannot scope an agent’s authority against a 47-step end-to-end process; you can scope it against an atom. Process atoms give us the unit of least privilege for the agentic era, the equivalent of granting a transaction code rather than SAP_ALL.
Rules: Company Memory
Company Memory is where the organization’s rules about what should happen live: the policies, constraints, and institutional knowledge that govern process execution. For utilities, this is where our regulatory obligations get encoded, such as the rule that a disconnect for non-payment cannot proceed during a medical-certificate hold, that a switching order requires specific approvals, and that certain customer data never leaves defined boundaries. In a human enterprise, these rules live in procedure manuals and tribal knowledge. In an autonomous enterprise, they must live somewhere agents can read them and governance functions can audit them. Company Memory is that home, which also makes it one of the most security-critical assets in the entire architecture: whoever can write to your rules can steer your agents.
Runtime: Process AI on Signavio
Rules are only as good as their enforcement. SAP Signavio’s Process AI watches what is actually happening during execution and compares it against what should be happening, conformance checking for a workforce that operates at machine speed. Signavio now supports agents as a documented role and swimlane in BPMN process models. That sounds like a modeling footnote; it is actually a compliance breakthrough. When your internal auditor or your regulator asks, “Where in this process does an AI agent act, and what are the controls around it?” you can now answer with a process diagram instead of a shrug.
Accountability: Agents in the Org Structure
Coming next quarter, SAP SuccessFactors will support organizational capabilities for agents, meaning agents will appear in the organizational structure, visible alongside the human workforce, with clarity about where they operate and who is responsible for them. Every utility security framework ultimately rests on accountability: every actor reports to someone. Placing agents in the org chart answers a question regulators will absolutely ask: who owns this agent? If an agent dispatches a crew incorrectly or mis-adjusts a rate, the accountability chain should be as traceable as it would be for an employee.
Verification: LeanIX AI Agent Hub and the Verification Seal
Also coming next quarter is the piece I find most significant: the LeanIX AI Agent Hub. It extends LeanIX’s enterprise architecture discovery to AI agents, giving architects an inventory of what agents exist and which business capabilities they touch. But the differentiator is the Verification Seal: agents that pass verification carry a seal that is then enforced in the Joule runtime. Unverified agents do not run.
This is the difference between governance as documentation and governance as control. Most AI governance frameworks today produce policies, registers, and review boards, paper controls that depend on humans remembering to follow them. A verification seal enforced at runtime is a technical control: the platform itself refuses to execute agents that have not passed through the governance gate. For utility CISOs, this is the architectural pattern we have been waiting for, the agentic equivalent of application allow-listing on a critical cyber asset.
The Honest Caveats
Embracing this direction does not mean accepting it uncritically, and three caveats deserve daylight.
First, several of these capabilities are roadmap, not product. The agentic reference architecture itself carries a disclaimer worth quoting in spirit: the Agent Gateway is not yet generally available, and the published architecture currently supports outbound communication only, with bidirectional capabilities expected soon. The SuccessFactors agent organizational capabilities and the LeanIX AI Agent Hub are slated for next quarter. Our community has learned to distinguish between announced, delivered, and adopted. Plan against the architecture; commit against shipped functionality.
Second, the shared responsibility line has not moved. RISE’s security framework explicitly leaves application-layer identity, authorizations, business process configuration, and regulatory compliance with the customer. Agents are application-layer actors. SAP is giving us better tools and better blueprints, but agent governance is our responsibility, not something we outsource with a cloud subscription.
Third, watch the commercial fine print. Some ECS security capabilities are included in the default RISE package; others, including SAP Enterprise Threat Detection, the engine at the heart of the published security operations architecture, carry separate costs. As agent governance tooling matures, we should push hard for the capabilities that make agents safe to be treated the way SAP itself describes its ECS philosophy: mandatory security features, no hidden security costs. Security for the autonomous enterprise cannot become an upsell.
What We Still Need to Influence
As with the broader Autonomous Enterprise vision, our community has both the standing and the responsibility to shape this:
- Extend the published security operations pattern to agents. The ETD-to-SIEM/SOAR reference architecture is exactly the right skeleton. We need SAP to extend it with agent-specific detection content, agent activity log sources, and the explicit guarantee that agent actions are distinguishable from human actions at every hop, from application log to SIEM event to SOAR case.
- Agent identity lifecycle guidance: SAP Cloud Identity Services already brokers trust across the agent architecture. What we need now is published guidance for agents as first-class identities, covering provisioning, credential rotation, certification, and deprovisioning, and integration with our existing IAM and PAM investments.
- SAP-aware response actions for agents: The SOAR pattern documents containment actions for human accounts: session termination, account locking, and role changes. We need the agent equivalents documented and supported in SOAR connectors: suspend an agent, quarantine its outputs, revoke its verification seal.
- Verification Seal transparency: What does verification actually test? Who can grant it, revoke it, and audit it? A runtime-enforced seal is only as trustworthy as the verification process behind it. The criteria must be transparent and customer-auditable.
- NERC CIP alignment guidance: We need SAP to publish explicit mapping between the agent governance stack and NERC CIP requirements, particularly around access management, change control, and evidence generation, so that each utility is not reinventing that analysis alone.
- Operational technology boundaries: Our most sensitive systems (ADMS, SCADA, OMS) sit outside SAP’s perimeter, but inside many of the workflows agents will touch. We need explicit architectural guidance on where agent authority stops at the OT boundary.
A Call to Our Community
Last month, I asked our community a hard question: if not SAP’s governance framework, then what? This month, I’ll ask its sequel: if your utility deployed an AI agent into production tomorrow, could you tell your regulator who authorized it, what rules it follows, who monitors it, where it sits in your organization, and how you would shut it down?
If the answer is no, that is not a reason to avoid the autonomous enterprise. It is the project plan, and unlike a year ago, the components now have published architectures behind them. A hardened RISE foundation with LogServ and RAVEN for visibility. A documented ETD-to-SIEM/SOAR pattern that puts SAP detections, agent telemetry, and the agent kill switch inside your existing SOC. A published agent architecture with identity-brokered trust at every connection. Process atoms for scoping, Company Memory for rules, Signavio Process AI for runtime conformance, organizational accountability in SuccessFactors, and runtime-enforced verification through LeanIX and Joule.
Our job is to assemble these into a governance posture our security teams, auditors, and regulators can stand behind, and to push SAP, loudly and constructively, where the gaps remain. Start with the two reference architectures on SAP’s Architecture Center. Hand them to your security architect and your SOC lead this week. They are free, current, and the starting point for the regulator conversation every one of us will eventually have.
Security is the precondition for the autonomous enterprise, not one of its features, and the utilities that treat it that way will be the ones whose agents make it out of the lab.
For more SAP utilities insights, sign up to receive ASUG’s free The Topic: Utilities newsletter, and to get involved and keep up with the latest, join ASUG’s Utilities Community. Connect with SAP teams across the utilities community as they explore AI adoption, clean core, data strategy, and more at SAP for Utilities, Presented by ASUG in San Antonio, October 6 – 9, 2026.
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