Digital Omnibus; EU AI Act Timeline and Enforcement Delay
The Digital Omnibus is a European Commission legislative package proposed in February 2025 that consolidates amendments to multiple digital regulations — including the EU AI Act,…
Resources
Insights on AI Governance & Compliance
Explore our latest resources and practical guides to navigate the evolving landscape of AI compliance and regulation.
LATEST RESOURCES
AESIA — Spanish AI Supervisory Authority and EU AI Act Enforcement
AESIA (Agencia Española de Supervisión de la Inteligencia Artificial) is Spain's national artificial intelligence supervisory authority, established under Royal Decree 729/2023 and operationally active since 2024.…
Model Drift: where documented performance stops matching operational reality
Model drift refers to the gradual degradation of an AI model's performance over time as the statistical properties of the real-world data it encounters in production…
AI Governance Profession — Emerging Field, Roles, and Competencies
AI governance as a profession refers to the emerging organizational function and career field dedicated to designing, implementing, operating, and auditing the systems, processes, and structures…
Multi-Agent System (MAS) — Governance of Collaborative AI Architectures
A multi-agent system (MAS) is an AI architecture in which multiple autonomous AI agents operate collaboratively to accomplish tasks that exceed the capability, scope, or efficiency…
Agent Orchestration — Governance of AI Delegation and Coordination
Agent orchestration is the coordination mechanism through which an orchestrator agent — typically a large language model with planning capability — decomposes a high-level goal into…
Agent Scope Limitation — Containment Controls for Agentic AI Systems
Agent scope limitation is the governance and engineering practice of explicitly constraining the permissions, tools, data access, and action capabilities available to an AI agent to…
Agentic AI Trust Gap — Governance Maturity vs. Deployment Speed
The agentic AI trust gap refers to the systematic disparity between the speed at which organizations are deploying agentic AI systems and the maturity of the…
Data Lineage — Provenance and Traceability for AI Training Data
Data lineage in AI systems refers to the documented record of where data originates, how it has been transformed, what processes have been applied to it,…
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