#ai-governance
The oversight, accountability, and controls that govern AI itself and make adoption safe to scale.
Tagged articles (46)
From Probable to Provable: What Automated Reasoning Means for the Board
Automated reasoning gives Boards access to proof, not probability. This article explains what it is, where it already operates, and why it changes governance.
AI and the Director: A Practical Playbook for Governing What You Can't Fully See
Directorial AI literacy is not technical fluency. It is four specific capacities that let directors interrogate maturity claims, assess real governance, and exercise independent judgement.
MCP Explained: The Agent Infrastructure Standard Boards Need to Understand
An agent that sees only the public internet is an expensive search engine. MCP connects agents to the proprietary systems that constitute advantage.
The Inference Migration: What Consumer Agents Mean for Enterprise AI's Next Phase
Consumers are already paying for always-on AI agents. That consumer-to-enterprise pipeline is the one ChatGPT ran, and it is running again.
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.
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