The paper argues for appointing a Chief AI Officer (CAIO) once artificial intelligence becomes strategic and impactful within organizations. It highlights the need for dedicated expertise in managing AI governance due to its complexity and rapid changes, asserting that executive attention is limited and current tech portfolios are overburdened.
The article discusses the lack of accountability and clarity in evaluating government algorithms, particularly regarding acceptable margins of error. It emphasizes the importance of understanding model performance, calibration, and the implications of error thresholds. The author advocates for explicit documentation of responsibility and evidence before deploying algorithms to enhance accountability.
Who signs off on a government algorithm’s margin of error? Read More »
Recent security reports reveal that while AI is not fundamentally transforming cyberattacks, it significantly accelerates existing methods, enabling attackers to operate at unprecedented scales. AI’s role is shifting from aiding preparation to executing operational tasks, raising challenges in governance, accountability, and speed that organizations must urgently address.
The Digital Omnibus is now law and defers the EU AI Act’s high-risk obligations to 2027 and 2028. The Article 50 transparency obligations still apply from 2 August 2026. For CEOs, the risk is not the deadline — it is mistaking a disclosure label for an output control.
