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.
Innovation here means shorter design cycles, not unreviewed code in production.
Innovation here means shorter design cycles, not unreviewed code in production.
Capabilities you use in iDataEngine
- Table/field recommendations
- AI Wizard for iDataView
- REP AI shortcut texts
- Session language-aware texts
- Human-in-the-loop Test gate
- AI management quotas
Recommended workflow
- Open the relevant cockpit (iDataView Explorer, SQL Project, API Service Detail, or AccessGuard).
- Configure source objects, fields, mappings, or rules using session language and customer/system context.
- 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 (2026)
An analyst describes a stock aging report in plain language; AI Wizard proposes tables and joins — consultant adjusts conditions, Test passes, Activate ships.
Why it matters
Quotas and admin controls let enterprises adopt AI without adoption becoming unbounded experiment cost.
Your next step is a controlled pilot: Test in cockpit, save with evidence, then extend to the next channel without redesign.