Runtime controls for SAP-connected AI

Policies written in a governance register only protect the business if they are enforced where AI actually acts. For SAP-connected AI — assistants and agents that can read, recommend and initiate actions across business processes — the decisive moment is the point of action: the instant an agent is about to post a transaction, change a record or trigger a downstream step. Runtime controls are the guardrails that check each of those actions against policy before it takes effect, so an out-of-policy or conflicting action is stopped rather than discovered afterward. This shifts governance from periodic review to continuous, in-line enforcement, which matters most precisely where AI touches systems of record.

Enforce policy at the point of action

The core idea is simple: every action an SAP-connected agent attempts is evaluated against the relevant policies at the moment it is attempted, and only allowed to proceed if it passes. The policies themselves come from the governance framework — the agent's permitted actions, its risk tier, the access and segregation-of-duties rules of the process it operates in, and any thresholds requiring human approval. Enforcing them at runtime means intent set in governance is actually honoured in production, not just documented.

Block SoD-violating and out-of-policy transactions

Two categories of action deserve particular attention. The first is anything that would breach segregation of duties — an agent attempting a combination of steps, such as both recording and authorising a transaction on the same asset, that a human in that role would be prevented from holding. The second is any transaction outside policy more broadly: beyond an approved value or scope, against a restricted vendor or account, or otherwise outside the agent's mandate. Runtime controls block these at the point of action, or route them to a human for authorisation, so a guardrail intervenes before harm is done rather than after.

Keep a complete audit trail

Enforcement is only half the requirement; you also have to be able to show what happened. Every action an agent attempts — allowed, blocked or escalated — should be logged with the policy it was checked against, the decision, and the link back to the agent, its owner and the process. A complete audit trail turns runtime enforcement into durable evidence: it lets the organisation demonstrate to auditors and regulators that SAP-connected AI operated inside its mandate, and it feeds the same control and evidence records that governance reporting and board packs draw on.

From policy to enforced practice

Runtime controls close the gap between a governance framework and what AI actually does in SAP. They keep the principles already established — accountability, risk-tiered controls, segregation of duties — in force at the moment they matter, consistent with the risk-management and accountability expectations in the OECD AI Principles, ISO/IEC 42001 and the NIST AI Risk Management Framework.