NoèmeX publishes guidance on evidence-based AI governance

NoèmeX today published new guidance on evidence-based artificial intelligence governance for executives, boards and technology leaders.

The guidance examines how organizations can distinguish an AI label from an evidenced capability. It connects capability claims with the underlying model behaviour, data, human oversight, monitoring, traceability and operating context required to evaluate them responsibly.

The publication considers governance across the system life cycle: defining the decision or action, validating the model and data, assigning decision rights, establishing approval and escalation paths, monitoring performance and recording evidence for review. It also addresses the relationship between technical assurance, privacy obligations and executive accountability.

The objective is to make AI governance operational: controls should correspond to the decisions a system influences, the actions it may take and the consequences that require human judgment or intervention.