#ai-governance
The oversight, accountability, and controls that govern AI itself and make adoption safe to scale.
Tagged articles (42)
The Invisible Asset: Why Boards Should Govern Data Like It's on the Balance Sheet
Boards steward physical assets with condition checks and ownership, and govern data as if it did not exist. The gap is governance, not technology.
Return-to-Work Briefing: Five Forces Reshaping the Board AI Agenda in 2026
Five forces shape the Board's AI agenda in 2026, led by AI embedding into the enterprise faster than it can be governed. None is distant.
Minimum Lovable Governance: The AI Operating Principle Boards Should Use
Minimum lovable governance replaces episodic compliance with continuous, embedded oversight people actually want to use: guardrails that earn adoption rather than enforce it.
The Accountability Gap: When AI Delegation Meets Human Responsibility
Organisations are transferring decision-making agency to AI while accountability stays with people, and approving deployments without the verification capability that accountability needs.
Orchestrating Multi-Speed AI: The Complete AI Framework as Guiding Policy
Most organisations use AI; few have redesigned the work around it. The Complete AI Framework is the guiding policy turning diagnosis into action.
AI's Interconnected Challenge: Diagnosing the Six Concerns of the Board
The Board's six concerns demand simultaneous orchestration and receive sequential, project-level attention. Treating them as one diagnostic lens is where AI governance starts.
After the AI Amnesty: Practical Steps to Operationalise Discovered Shadow AI
After the amnesty, speed matters: employees who disclosed expect enablement, not restriction. A roadmap for turning discovered shadow AI into governed capability.
Shadow AI and the Case for an AI Amnesty
Shadow AI is surging and most employees would use AI tools without permission. An AI amnesty turns that hidden risk into governed, employee-validated innovation.
AI Sovereignty: A Board's Guide to Navigating Conflicting National Agendas
AI governance is fragmenting into incompatible systems: Europe's transparency, America's scale, China's control. Boards can no longer serve all three; they have to choose.
Crossing the GenAI Divide: Solving The 95% Problem With The Complete AI Framework
MIT confirms what I have argued since 2024: 5% of organisations take generative AI from pilot to production. The Complete AI Framework answers that divide.
Why Boards Need to Watch the EU's General-Purpose AI Code of Practice
The EU's General-Purpose AI Code of Practice marks regulatory divergence: Europe sets transparency guardrails while America deregulates. Boards must now choose between transparency and speed.
AI Centre of Excellence: Future-proofing Through Continuous Evolution
The AI landscape moves faster than any governance framework. An AI Centre of Excellence stays relevant only if continuous evolution is designed in.
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