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Glossary

Industrial AI Readiness Glossary

Public-safe definitions for the readiness pillars, evidence terms, exported-data inputs, source-context concepts, diagnostic outputs, and review language behind AI2COE research.

50 termsConcise definitions
Dictionary-derivedPublic-safe only
No benchmark outputsDefinitions and methodology
Executive takeaway

Research benchmark

Industrial AI Readiness Glossary: This research page frames the operating hypothesis, assumption boundary, and diagnostic path needed before transformation spend. Concise public definitions for Industrial AI Readiness, evidence standards, data exports, readiness pillars, diagnostic outputs, and review concepts.

Run Free Industrial IQ Snapshot
Who should use itExecutives and analysts sizing an operating hypothesis before replacing benchmark assumptions with uploaded-data evidence.
Data requiredBenchmark assumptions until replaced by uploaded customer data from an Industrial IQ diagnostic.
Output producedA research interpretation that separates benchmark logic, assumptions, limitations, and the recommended diagnostic path.
Best next stepUse the benchmark as a hypothesis, then replace it with uploaded-data evidence.
Short answer

A public language layer for Industrial AI Readiness.

This glossary provides concise, LLM-friendly definitions for public research and buyer education. It is derived from the AI2COE Knowledge Dictionary but excludes internal governance notes, private relationship matrices, and unpublished backlog details.

Publication boundary: These are definitions and methodology terms, not measured benchmark outputs, private buyer evidence, compliance status, or financial outcome statements.
Core research links

Use the glossary with the framework, methodology, and evidence standards.

Glossary terms

Public-safe terms for buyers, reviewers, and AI assistants.

Industrial AI Readiness

Industrial AI Readiness

Definition: The ability to support industrial AI decisions with usable operational data, governed source boundaries, evidence classes, confidence tiers, and human review.

Why it matters: It helps leaders decide whether AI work has enough operational evidence before implementation.

Related asset: /research/industrial-ai-readiness/framework

Governance Readiness

Industrial Decision Intelligence

Definition: A diagnostic category focused on turning operational data into evidence-backed findings, scores, reports, and owner-reviewed actions.

Why it matters: It frames Industrial IQ as evidence before transformation, not autonomous remediation.

Related asset: /solutions/industrial-ai-readiness

Operational Readiness

Industrial IQ

Definition: AI2COE's Industrial Decision Intelligence platform for read-only diagnostics, evidence-backed findings, report packs, and governed action tracking.

Why it matters: It gives buyers a controlled diagnostic path before ERP, MRO, inventory, procurement, or AI changes.

Related asset: /solutions/industrial-ai-readiness

Data Readiness

Data Readiness

Definition: The condition of operational data being complete, interpretable, traceable, and fit for diagnostic use.

Why it matters: Data readiness determines whether findings can be trusted enough for review.

Related asset: /research/industrial-ai-readiness/assessment-methodology

Operational Readiness

Operational Data Readiness

Definition: The readiness of plant, asset, maintenance, procurement, inventory, and source-system data for operational decision support.

Why it matters: It connects data quality to operating decisions rather than abstract data maturity.

Related asset: /research/industrial-ai-readiness/assessment-methodology

ERP Readiness

ERP Readiness

Definition: The ability of ERP records and exports to support diagnostics, migration planning, cleanup, reporting, or AI use without uncontrolled source-system change.

Why it matters: ERP readiness reduces transformation risk before migration or automation decisions.

Related asset: /solutions/industrial-ai-readiness

ERP Readiness

SAP Readiness

Definition: The readiness of SAP-related exports, material records, plant context, and governance fields for diagnostic interpretation.

Why it matters: It helps SAP teams review data quality before migration, cleanup, or AI initiatives.

Related asset: /solutions/sap-material-master-cleanup

Material Master Readiness

SAP Material Master

Definition: The SAP record structure used to identify, describe, classify, and manage materials across plants and business processes.

Why it matters: It is often the source of MRO, inventory, procurement, and readiness evidence.

Related asset: /solutions/sap-material-master-cleanup

Material Master Readiness

Material Master Readiness

Definition: The condition of material or item master records being usable for search, mapping, duplicate review, procurement interpretation, and readiness assessment.

Why it matters: It supports cleaner decisions before master-data remediation or ERP migration.

Related asset: /research/industrial-ai-readiness/framework

MRO Readiness

MRO Readiness

Definition: The readiness of maintenance, repair, and operations data across catalogs, inventory, procurement, assets, and work-order context.

Why it matters: It shows whether spare-parts decisions can be supported by evidence.

Related asset: /mro-catalog-intelligence

MRO Readiness

MRO Data Quality

Definition: The condition of MRO records being descriptive, consistent, traceable, and useful for catalog, inventory, procurement, and maintenance review.

Why it matters: MRO data quality is a readiness signal for AI, ERP, and operational decisions.

Related asset: /sap-maximo-oracle-mro-data-quality

Inventory Readiness

Inventory Readiness

Definition: The readiness of inventory records to support review of stock levels, movement history, criticality, excess, obsolescence, and false-stockout signals.

Why it matters: It helps operations and finance inspect inventory risk before action.

Related asset: /solutions/inventorymind-ai

Inventory Readiness

Inventory Trust

Definition: The level of confidence that inventory records can support decisions after source-fit, context, and owner review.

Why it matters: It prevents inventory data from being treated as reliable without evidence.

Related asset: /inventory-intelligence

Inventory Readiness

Inventory Capital Exposure

Definition: A diagnostic interpretation of inventory value and carrying assumptions that may require finance review.

Why it matters: It helps CFOs review capital tied to MRO inventory without treating estimates as outcomes.

Related asset: /solutions/financemind-ai

Asset Readiness

Critical Spare Readiness

Definition: The ability to identify and review spare parts that may matter for uptime, shutdown readiness, or maintenance continuity.

Why it matters: It helps reliability and maintenance leaders prioritize evidence review.

Related asset: /solutions/reliabilitymind-ai

Procurement Readiness

Procurement Readiness

Definition: The readiness of procurement, supplier, contract, and purchase records for leakage, variance, emergency-buy, and governance review.

Why it matters: It helps CPOs evaluate whether procurement data supports defensible action.

Related asset: /solutions/procuremind-ai

Procurement Readiness

Procurement Leakage

Definition: A diagnostic concept for potential value leakage caused by supplier fragmentation, repeated buys, emergency purchases, or inconsistent purchasing context.

Why it matters: It helps procurement leaders focus review on evidence-backed exceptions.

Related asset: /solutions/procuremind-ai

Asset Readiness

Asset Readiness

Definition: The readiness of asset, equipment, BOM, hierarchy, and spare-part relationship data for diagnostic interpretation.

Why it matters: It helps maintenance and reliability teams connect parts decisions to physical assets.

Related asset: /solutions/assetmind-ai

Operational Readiness

Maintenance Readiness

Definition: The readiness of work-order, spare-parts, asset, priority, and maintenance-history data for operational review.

Why it matters: It supports maintenance decisions before readiness gaps affect work execution.

Related asset: /solutions/reliabilitymind-ai

Governance Readiness

Governance Readiness

Definition: The readiness of review ownership, evidence boundaries, audit metadata, and decision controls for governed action.

Why it matters: It helps buyers act on findings without uncontrolled remediation.

Related asset: /solutions/governancemind-ai

AI Governance Readiness

AI Governance Readiness

Definition: The readiness of AI-related decisions to use evidence classes, confidence tiers, human review, and source-system boundaries.

Why it matters: It keeps AI adoption accountable and explainable.

Related asset: /research/industrial-ai-readiness/evidence-standards

Governance Readiness

Evidence Classification

Definition: The method of labelling evidence as Observed, Derived, Estimated, or Hypothesis.

Why it matters: It prevents assumptions, methodology, and direct evidence from being treated as the same proof level.

Related asset: /research/industrial-ai-readiness/evidence-standards

Governance Readiness

Observed Evidence

Definition: Evidence directly traceable to a verified source row, field, route, approved diagnostic output, or approved internal artifact.

Why it matters: It is the strongest evidence class for review because the source can be traced.

Related asset: /research/industrial-ai-readiness/evidence-standards

Governance Readiness

Derived Evidence

Definition: A finding or definition inferred from approved methodology, mapped fields, research structure, and industrial operating logic.

Why it matters: It supports interpretation when the reasoning path is visible.

Related asset: /research/industrial-ai-readiness/evidence-standards

Governance Readiness

Estimated Evidence

Definition: An assumption-based score, exposure band, planning range, or directional signal that requires clear assumption boundaries.

Why it matters: It helps planning while preventing estimates from being treated as measured facts.

Related asset: /research/industrial-ai-readiness/evidence-standards

Governance Readiness

Hypothesis Evidence

Definition: A candidate finding, future benchmark idea, proposed threshold, or research direction requiring validation before decision use.

Why it matters: It keeps future ideas separate from approved diagnostic evidence.

Related asset: /research/industrial-ai-readiness/evidence-standards

Governance Readiness

Confidence Tier

Definition: A review label that indicates how strongly available evidence supports a finding or interpretation.

Why it matters: It helps owners prioritize which findings are ready for review and which need more context.

Related asset: /research/industrial-ai-readiness/assessment-methodology

Data Readiness

Source Fit

Definition: A measure of whether an exported source contains the fields, identifiers, context, and quality needed for diagnostic interpretation.

Why it matters: It helps teams understand whether the upload can support confident findings.

Related asset: /research/industrial-ai-readiness/assessment-methodology

Data Readiness

Source-Fit Review

Definition: A review step that checks exported data against required fields, optional context, identifiers, and diagnostic use.

Why it matters: It reduces the risk of interpreting weak inputs too strongly.

Related asset: /research/industrial-ai-readiness/assessment-methodology

Data Readiness

Field Mapping

Definition: The process of matching uploaded columns to diagnostic concepts such as material ID, supplier, stock value, work order, plant, or asset.

Why it matters: It turns source exports into usable diagnostic inputs.

Related asset: /research/industrial-ai-readiness/assessment-methodology

Data Readiness

Data Template

Definition: A starter structure showing useful fields for a diagnostic engine or readiness assessment.

Why it matters: It helps teams prepare exports without requiring source-system integration.

Related asset: /resources/data-templates

ERP Readiness

ERP Export

Definition: A data extract from ERP records such as material master, inventory, procurement, plant, or finance context.

Why it matters: It lets ERP teams review readiness without changing the ERP system.

Related asset: /erp-data-quality-for-ai

Asset Readiness

EAM Export

Definition: A data extract from enterprise asset management records such as assets, equipment hierarchy, BOM, work orders, or parts.

Why it matters: It supports asset and maintenance readiness diagnostics.

Related asset: /solutions/maximo-item-master-cleansing

Operational Readiness

CMMS Export

Definition: A data extract from maintenance systems with work orders, assets, tasks, priorities, failures, or parts usage.

Why it matters: It helps maintenance teams review operational readiness from existing records.

Related asset: /solutions/reliabilitymind-ai

Procurement Readiness

Procurement Export

Definition: A data extract containing purchase orders, suppliers, contracts, prices, lead times, or emergency-buy indicators.

Why it matters: It supports procurement readiness and leakage review.

Related asset: /solutions/procuremind-ai

Inventory Readiness

Inventory Export

Definition: A data extract containing stock quantity, stock value, storage location, movement, criticality, and replenishment context.

Why it matters: It supports inventory readiness and exposure review.

Related asset: /solutions/inventorymind-ai

Asset Readiness

Asset Register

Definition: A structured list of assets, equipment, locations, identifiers, and related operating context.

Why it matters: It supports asset-to-part linkage and maintenance readiness review.

Related asset: /solutions/assetmind-ai

Asset Readiness

BOM Coverage

Definition: The degree to which equipment or asset records are connected to bill-of-materials and spare-part relationships.

Why it matters: It helps teams understand whether asset data supports spare-parts decisions.

Related asset: /solutions/assetmind-ai

Material Master Readiness

Item Description Quality

Definition: The usefulness and consistency of item descriptions for search, duplicate review, classification, and diagnostic interpretation.

Why it matters: It affects catalog cleansing, procurement review, and material master readiness.

Related asset: /solutions/partscleanse-ai

Material Master Readiness

Manufacturer Ambiguity

Definition: Unclear, inconsistent, or missing manufacturer and manufacturer-part information in item or material records.

Why it matters: It can reduce duplicate-detection confidence and catalog searchability.

Related asset: /solutions/partscleanse-ai

Material Master Readiness

Unit of Measure Inconsistency

Definition: A mismatch or inconsistency in units of measure across items, plants, suppliers, or purchasing records.

Why it matters: It can affect duplicate review, procurement interpretation, and inventory analysis.

Related asset: /solutions/partscleanse-ai

Procurement Readiness

Contract Context

Definition: Contract identifiers, terms, supplier relationships, or buying context used to interpret procurement records.

Why it matters: It helps procurement exceptions be reviewed with commercial context.

Related asset: /solutions/procuremind-ai

Inventory Readiness

Lead-Time Context

Definition: Replenishment or supplier timing information used to interpret stock, procurement, and critical-spare readiness.

Why it matters: It helps distinguish normal replenishment risk from urgent operational exposure.

Related asset: /solutions/inventorymind-ai

Operational Readiness

Plant Context

Definition: Plant-level identifiers and operating context that explain where inventory, materials, assets, and purchases apply.

Why it matters: It prevents multi-site records from being interpreted without local operating context.

Related asset: /research/industrial-ai-readiness/assessment-methodology

Operational Readiness

Site Context

Definition: Site or location context that explains where assets, stores, work orders, procurement, and inventory records belong.

Why it matters: It supports source-fit and owner review for distributed operations.

Related asset: /research/industrial-ai-readiness/assessment-methodology

Data Readiness

Source Context

Definition: The metadata, ownership, system origin, field meaning, plant, site, contract, and timing context needed to interpret exported records.

Why it matters: It improves diagnostic interpretation while preserving evidence boundaries.

Related asset: /research/industrial-ai-readiness/evidence-standards

Governance Readiness

No ERP Write-Back

Definition: A trust boundary where diagnostics use exported data and do not write changes back to ERP, EAM, CMMS, or source systems.

Why it matters: It lowers operational risk and keeps remediation buyer-controlled.

Related asset: /trust/no-erp-writeback

Governance Readiness

Source-File Purge

Definition: The handling principle that uploaded source files are processed to generate a diagnostic report pack and then purged.

Why it matters: It clarifies upload lifecycle while preserving governance metadata boundaries.

Related asset: /trust/data-retention

Governance Readiness

Human Review

Definition: The requirement that accountable owners review findings before action, remediation, or source-system change.

Why it matters: It keeps diagnostic outputs governed and buyer-controlled.

Related asset: /research/industrial-ai-readiness/evidence-standards

Operational Readiness

Diagnostic Report Pack

Definition: A package of findings, scores, evidence tables, assumptions, exclusions, and recommended review actions generated from a diagnostic.

Why it matters: It helps buyers review evidence before operational action.

Related asset: /platform/sample-reports

FAQ

Glossary boundaries.

Is this the full AI2COE Knowledge Dictionary?

No. This public glossary uses concise definitions derived from the Knowledge Dictionary, but it does not expose internal governance notes, relationship matrices, or future backlog details.

How should buyers use the glossary?

Use it to understand Industrial AI Readiness terms before reviewing the framework, assessment methodology, evidence standards, or diagnostic hub.

Are glossary definitions measured benchmark outputs?

No. They are public-safe definitions and methodology explanations. Benchmark reporting requires approved evidence thresholds and review.

Why do exported-data terms matter?

Industrial IQ diagnostics start from exported operational data, so buyers need clear language for CSV, ERP, EAM, CMMS, procurement, inventory, and source-context inputs.

Does the glossary imply source-system integration?

No. Data export terms describe source inputs for diagnostics. They do not imply ERP write-back or live system integration.