How this diagnostic works for a decision owner.
| Readiness label | Public synthetic demonstration |
|---|---|
| Business problem | ERP data quality, governance readiness, operational readiness, and first-use-case recommendation. |
| Buyer role | CIO, CTO, COO, Data Governance, and AI Transformation leaders |
| Trigger event | ERP readiness review, first AI use case selection, migration readiness, export completeness, or data quality governance pressure. |
| Core source export | Process Name, Data Source |
| Optional fields | Business Unit, Data Owner, Data Quality Score, System Of Record, Automation Readiness, Governance Owner, Ai Use Case, Risk Level, Site, Owner, Approval Status, Last Updated |
| Upload workflow | Upload -> Validate -> Analyze -> Evidence -> Score -> Report -> Action -> Repeat |
| Column mapping | Industrial IQ profiles source-fit, suggests field matches, asks the user to normalize unmapped required fields, then recalculates mapping readiness before the engine runs. |
| Evidence generated | Source-backed evidence rows, reason codes, confidence tiers, review status, assumptions, limitations, and action-owner context. |
| Score output | AI readiness score |
| Report output | ReadyMind AI AI Readiness Report |
| Confidence tiers | High-confidence findings can move to review; weak or unsafe matches stay in human-review queues. |
| Recurring use case | Monthly or quarterly re-uploads create score history, action progress, planning comparison, and renewal value reporting. |
Minimum viable fields and engine-specific context.
| Engine | Required Data File | Required Fields | Optional Fields | Output Generated | Minimum Viable Upload | Engine-Specific Context |
|---|---|---|---|---|---|---|
| ReadyMind AI | ERP export sample | Process Name, Data Source | Business Unit, Data Owner, Data Quality Score, System Of Record, Automation Readiness, Governance Owner, Ai Use Case, Risk Level | AI readiness score, evidence, report, actions, score history | Process Name, Data Source | Business Unit, Data Owner, Data Quality Score, System Of Record, Automation Readiness, Governance Owner, Ai Use Case, Risk Level |
What this engine analyzes.
- ERP data quality, data freshness, owner accountability, governance readiness, and first-use-case recommendation.
- Field completeness, consistency, duplicate-rate, site context, valuation, and review workflow scoring.
- ERP/AI readiness output that labels what is proven, missing, assumed, and blocked.
How the engine matures after the first run.
- ERP-specific readiness pack for SAP, Maximo, Oracle, Infor, Hexagon EAM, and CMMS exports.
- Transformation risk register and first-use-case sequencing across PartsCleanse, InventoryMind, ProcureMind, and ReadyMind.
- AI adoption roadmap grounded in uploaded-data readiness instead of generic AI maturity claims.
- Industry planning comparison for data, ERP, governance, and AI readiness.
- Transformation sequencing engine with budget, risk, and data-readiness gates.
- Recurring readiness trend for quarterly steering committees.
How to read the output.
ReadyMind AI AI Readiness Report includes AI readiness score, evidence records, confidence tiers, assumptions, limitations, action tracker items, score history, and no-write-back governance language.
How this connects to AI2COE Industrial IQ
AI Readiness Intelligence is not treated as an isolated content topic. Industrial IQ connects it to uploaded data, engine evidence, confidence tiers, executive reports, actions, score history, and governance review.