Assessment framework
Trustworthy AI Maturity Model (TAIMM)
TAIMM translates EU trustworthy AI principles and governance obligations into
structured questionnaires for AI system context, design, development and operation.
It gives teams a consistent way to record evidence, assess maturity and identify
gaps across the AI lifecycle.
Lifecycle-aligned assessment
Evidence and rationale capture
Governance maturity reporting
TAIMM was developed through Louise McCormack's doctoral research with the ADAPT
Centre at the University of Galway. Access to an assessment workspace uses Google
sign-in followed by an organisation activation key.
Online course · 5 lectures · 30 minutes
Operationalising Trustworthy AI
Course 1: Engineering Governance with Data, Traceability and Automation
This introductory course explains the move from document-based governance and
periodic audits towards connected governance data, lifecycle traceability,
automated evidence collection and continuous assurance.
AI governance foundations
Assurance across the AI lifecycle
Evidence engineering and automation
Controls and evidence in AI engineering workflows
Created by Louise McCormack and developed by the Irish Alliance for Trustworthy AI.
It is suitable for governance, risk and compliance professionals, engineers,
architects, data scientists, MLOps practitioners and technical product teams.
Basic AI knowledge is helpful, but programming experience is not required.
