Large Language Model (LLM) — Governance and Regulatory Obligations
A Large Language Model (LLM) is a type of deep learning AI model trained on large-scale text corpora to understand, generate, and transform natural language. LLMs…
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
Privacy by Design — Integrating Data Protection into AI Systems
Privacy by Design (PbD) is the principle and practice of integrating data protection and privacy considerations into the design of systems, processes, and products from the…
Pseudonymization — Privacy Protection Technique for AI Training Data
Pseudonymization is a data processing technique defined in GDPR Article 4(5) as the processing of personal data in such a way that it can no longer…
Adversarial Attack — Deliberate Manipulation of AI Systems
An adversarial attack is a deliberate attempt to manipulate an AI system's behavior by crafting inputs that cause the model to produce incorrect or attacker-desired outputs,…
Agentic AI Governance Framework — AIGN Framework 1.0 and EU AI Act
An Agentic AI Governance Framework is a structured set of principles, requirements, and controls specifically designed for the governance of autonomous and multi-agent AI systems —…
AI Monitoring Challenges — NIST AI 800-4 Six-Category Framework
AI monitoring challenges refers to the structured set of difficulties that organizations encounter when attempting to maintain effective oversight of AI systems after deployment in production…
Jailbreaking — AI Safety Bypass and Resistance Controls
What is jailbreaking in AI systems? Jailbreaking is the practice of crafting inputs that bypass an AI system's safety controls, causing the model to produce content…
Technical Documentation — EU AI Act Annex IV Requirements
Technical documentation, in the context of the EU AI Act, refers to the comprehensive set of documents that providers of high-risk AI systems must prepare and…
Agentic AI — Autonomous AI Systems and Governance Implications
What is Agentic AI? Agentic AI refers to AI systems that can plan, make decisions, and execute sequences of actions autonomously to achieve specified goals, without…
Data Governance — Foundation of Trustworthy AI Systems
Data governance is the organizational framework of policies, processes, standards, roles, and controls that determines how data is collected, stored, managed, used, shared, and retired across…
Post-Market Monitoring — Ongoing AI System Compliance Surveillance
Post-market monitoring (PMM) is the systematic, ongoing process of collecting, documenting, and analyzing data about the performance, reliability, and behavior of AI systems after they have…
Grounding — Source-Anchored Generative AI for Regulated Workflows
What is grounding in generative AI systems? Grounding is the engineering practice of constraining a generative model's output to verifiable sources. Instead of relying on the…
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