Organisations that run SAP sit on some of the best-structured business data there is. That makes them well placed to benefit from generative AI, provided they start where value is clear and risk is manageable. These are the use cases we see paying off first.
1. Invoice and document processing
AI reads supplier invoices, delivery notes and orders in any layout, extracts the data, checks it against purchase orders and master data in SAP, and prepares the posting. People review only the exceptions.
2. Finance close commentary
AI drafts variance explanations and management commentary from SAP figures, which controllers then review and refine. It saves hours at every month-end.
3. Procurement assistants
Buyers ask in plain language about suppliers, contracts and spend, and the assistant answers from SAP and contract documents with citations.
4. Service and order desks
Agents read customer emails, check order status in SAP, and draft replies or create cases, so service teams answer faster.
5. Master data quality
AI flags duplicate vendors, inconsistent material descriptions and missing fields, and suggests corrections for data stewards to approve.
6. SAP support and knowledge
A knowledge assistant trained on your SAP documentation, past tickets and process guides helps users and support teams resolve issues without waiting.
What every use case needs
- Secure, permission-aware access to SAP data through standard APIs
- A clear human review step where postings or customer messages are involved
- An evaluation set that proves accuracy before go-live
- A named business owner who tracks the value
AI Readiness Assessment
Two weeks, fixed scope: ranked AI use cases, data and risk check, and a pilot plan.
See what's included
