A non-customer illustrative scenario showing how Industrial IQ assesses ERP data readiness, governance ownership, and first-use-case fit before AI adoption.
A CIO and transformation team need to know whether operational data is ready for AI use cases before funding copilots, predictive workflows, or decision automation.
| Finding | Illustrative interpretation |
|---|---|
| Missing owner | Core maintenance and material fields have no accountable data owner. |
| Weak relationship integrity | Assets, BOMs, and materials do not support a reliable first AI use case. |
| Governance gap | Review status and audit trail fields are not ready for decision automation. |
AI adoption can scale poor operational evidence faster if readiness, ownership, and review boundaries are not proven first.
No ERP write-back. Source files purged after report generation. Human review before action. Summary metrics and audit metadata may be retained for governance.
No. It is an illustrative diagnostic scenario for buyer evaluation and does not use customer data or customer claims.
Industrial IQ replaces sample findings with uploaded-data evidence, confidence tiers, scores, reports, and action ownership.
No. It produces evidence for human review and does not change ERP, EAM, CMMS, procurement, inventory, or maintenance systems.
Resource review reduces friction: what data is needed, how reports look, how evidence is reviewed, and which route the buyer can take next.
Implementation leads, buyer committees, data owners, procurement reviewers, and product champions.
Required fields, CSV templates, user manuals, buyer guides, sample reports, diagnostic scenarios, and trust controls.
A prepared evaluation path that leads to sample proof, data templates, upload, or a scoped diagnostic discussion.
Read-only diagnostics, no ERP write-back, source-file purge after report generation, and human review before action.