Many ERP AI initiatives fail because they start with technology rather than a workflow bottleneck. The right first step is finding repetitive decisions where data already exists but decisions are still manual.
High-impact starting points include demand forecasting, anomaly detection, ticket triage, and document classification. Each can be deployed incrementally and measured against cycle-time and error-rate metrics.
A successful rollout depends on integration discipline: clean data pipelines, human override controls, and clear ownership across operations and IT teams. AI should improve ERP reliability, not add complexity.