AI Management: Models, Quotas and Guardrails addresses a problem most SAP landscapes know too well: Generic AI hype falls flat in SAP without recommendations grounded in your real tables and a human approval step before anything goes live.
AI usage is governed centrally with model and quota controls, and every recommendation respects your organization's data boundaries and session language.
AI in iDataEngine recommends tables and fields, powers the iDataView Wizard, assists BI view design, and proposes safe custom table structures — always with a human Test and Activate step before anything goes live.
Capabilities you use in iDataEngine
- Session language-aware texts
- Safe custom table naming checks
- REP AI shortcut texts
- Table/field recommendations
- Module and join suggestions
- Human-in-the-loop Test gate
Recommended workflow
- Run Test (iDataView Test, SQL First Row, API Test Service, or AG scan) before scheduling or publishing.
- Open the relevant cockpit (iDataView Explorer, SQL Project, API Service Detail, or AccessGuard).
- Extend the same definition to the next channel (API, SQL, MF, BI) without redesigning from scratch.
- Enable monitoring alerts and review dashboard KPIs for the first production cycle.
Real-world scenario (2021)
BI designer uses AI layout suggestion, then publishes under auth fields — speed without bypassing role review.
Why it matters
Quotas and admin controls let enterprises adopt AI without adoption becoming unbounded experiment cost.
Innovation here means business sees results faster — IT keeps control because every step is configured, tested, and monitored.