iristam.ai · AI Strategy & Governance

AI Readiness Self-Assessment

Most AI projects fail not because of the technology, but because of gaps in data, process, governance, and people. This assessment identifies where your organisation stands across all four dimensions.

20 questions4 dimensions~5 minutes

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Dimension 01 / 04

Data Readiness

AI is only as reliable as the data it reads. Most organisations discover data quality issues only after deployment, when the cost of fixing them is highest.

Unstructured data is AI-readable
PDFs, audio, invoices, and scanned documents have been converted into formats an AI can process without manual intervention.
Data formats are consistent and clean
Fields use standardised naming, types, and encoding. The AI does not need pre-processing scripts to interpret inputs.
A retrieval system (RAG or knowledge base) is in place
Internal knowledge such as policies, playbooks, and historical records is indexed and retrievable by AI with measurable accuracy.
Data is kept current through an update mechanism
There is a defined process and owner for refreshing datasets. The AI cannot silently drift on stale information.
Core business data is classified and labelled
Datasets are tagged by type, sensitivity, and intended use, enabling the AI to retrieve the right information with precision.

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