AI Governance
The set of policies, processes, and infrastructure that determine how an organisation develops, deploys, and oversees artificial intelligence systems.
AI governance addresses the unique challenges of governing artificial intelligence. These challenges include:
- Speed: AI agents can take hundreds of actions per minute, faster than humans can review - Opacity: AI decision-making can be difficult to understand or explain - Scale: AI systems can affect thousands of people simultaneously - Autonomy: AI agents can act without human intervention - Learning: AI systems can change their behaviour over time
AI governance is a subset of corporate governance — it's not a separate discipline. The same principles apply (authority, accountability, oversight, evidence), but the mechanisms must operate at machine speed.
The AI governance landscape is evolving rapidly. The EU AI Act, various US state regulations, and emerging international standards are creating new obligations. Organisations that don't have AI governance infrastructure will face increasing regulatory and liability risk.
How Constellation handles this
Constellation treats AI governance as a subset of corporate governance, not a separate discipline. The same governance gate that enforces human constraints enforces AI constraints — unified governance infrastructure for the entire institution.
Frequently Asked Questions
What is the difference between AI governance and AI safety?
AI safety focuses on making AI systems technically safe (reducing harmful outputs, preventing misuse). AI governance focuses on how organisations manage and oversee AI systems institutionally (authority, constraints, accountability, oversight). Safety is a technical discipline; governance is an institutional one.