IT Acronym Dictionary
AI Governance, Responsible AI, and Shadow IT Acronyms

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AI (Artificial Intelligence):
Technology that enables systems to perform tasks associated with human reasoning, learning, prediction, language, or decision support

AIBOM (AI Bill of Materials):
An emerging inventory concept documenting the models, data sources, components, dependencies, and third-party services used in an AI system

AIMS (Artificial Intelligence Management System):
The management system used to govern AI policies, roles, controls, risks, monitoring, and continual improvement

AI RMF (AI Risk Management Framework):
A structured framework for identifying, assessing, managing, and governing AI-related risks across the AI lifecycle

CAIO (Chief Artificial Intelligence Officer):
A senior executive or leadership role responsible for enterprise AI strategy, governance, adoption, and value realization

DPIA (Data Protection Impact Assessment):
A privacy risk assessment used when systems, including AI systems, may significantly affect personal data or individual rights

GPAI (General-Purpose AI):
AI systems or models capable of supporting a wide range of tasks, often requiring extra governance because they can be reused across many business contexts

GenAI (Generative Artificial Intelligence):
AI that creates new content such as text, images, code, audio, video, summaries, or recommendations

HITL (Human in the Loop):
A governance and control approach where people review, approve, correct, or override AI outputs before important decisions are made

LLM (Large Language Model):
An AI model trained on large volumes of text that can generate, summarize, classify, translate, and reason over language-based information

ML (Machine Learning):
A branch of AI where systems learn patterns from data to make predictions, classifications, recommendations, or decisions

MLOps (Machine Learning Operations):
Practices for deploying, monitoring, updating, and governing machine learning models in production environments

RAI (Responsible AI):
An organizational approach to ensuring AI is used in ways that are fair, transparent, accountable, secure, privacy-aware, and aligned with business values

RAG (Retrieval-Augmented Generation):
An AI architecture that combines generative AI with trusted enterprise information sources to improve relevance, accuracy, and traceability

Shadow AI (Shadow Artificial Intelligence):
AI tools, models, agents, or AI-enabled workflows used without formal IT, security, legal, data, or governance approval

Shadow IT (Shadow Information Technology):
Technology acquired, developed, or used by business teams without formal IT involvement, review, or operational support

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