Useful AI in ERP should explain variances, detect anomalies, summarize risks, and cite operational data. It should not be a generic chatbot bolted onto a database.
The useful AI test
The question is not whether an ERP has AI. The question is whether AI reduces operational uncertainty without hiding the source data. A manufacturing user needs answers that reference invoices, stock movements, work orders, NCRs, suppliers, or customer records.
High-value AI use cases
- Explain invoice variance and payment risk.
- Detect unusual stock movement, scrap, or reject patterns.
- Suggest reorder actions based on demand and lead time.
- Summarize customer risk before confirming a large order.
- Explain production bottlenecks from capacity and work order data.
- Draft NCR, CAPA, and root-cause notes from structured evidence.