July 8, 2026
When AI becomes cultural habit rather than a tool
The operational adaptations described in the previous post rarely remain temporary. Over time, they harden into culture. Culture itself does not...
June 29, 2026
When AI fails in practice: The operational reality leaders need to address
In the previous article, we introduce how AI-enabled systems go through a use misuse, disuse and abuse cycle. This post examines how AI-enabled...
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June 24, 2026
Use, misuse, abuse and disuse: Why human intent breaks AI assurance models
This article is part of a series exploring why AI assurance fails in practice; not because models break, but because human intent, culture and...
June 17, 2026
Why management systems fall short for high-stakes AI governance
AI Assurance needs more than a management system.
June 12, 2026
When human oversight isn’t enough: Governing AI in the real world
Human-in-the-loop AI sounds reassuring. It suggests that automation is not being left alone, that professional judgement remains in control, and that...
June 8, 2026
AI assurance is looking in the wrong place
The easiest way to make AI assurance look rigorous is to focus on the model.
June 4, 2026
Accuracy is not assurance: Why AI test and evaluation is only the starting point
Test and evaluation is essential before deploying any trained AI system. It gives developers, buyers, and users evidence of how a model performs...
June 1, 2026
Assurance: Why defence risks turning it into governance theatre
Why AI impact assessments validate delivery instead of shaping design AI impact assessments are intended to influence decisions. In practice, they...
May 1, 2026
Accountability is a design property: Assurance and liability in high-stakes AI
Policy debates about AI often start where the damage ends: with liability after harm. Liability matters, but it is not enough on its own. When AI...
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