AI governance: Technical

Sefism.

A to Z

Glossary

Every concept in this sheet, plus the smaller terms it uses. Select a concept to open its card.

A
AI Act risk tiers
Four levels: unacceptable (banned), high risk (strict requirements such as risk management, data governance, logging, oversight and accuracy), transparency risk (disclose AI use or generated content) and minimal risk (no new duties).
AI governance
How an organisation decides which AI it builds or uses, who owns each system, which risks it accepts and what evidence shows its controls work.
AI inventory
A maintained list of every AI system an organisation builds, buys or uses, with purpose, owner, data, vendor, affected people, legal role, risk tier and review dates.
AI system
In the EU AI Act, following the OECD: a machine-based system that works with some autonomy and infers from inputs how to produce outputs such as predictions, content, recommendations or decisions.
E
EU AI Act
The EU law that regulates AI by risk, with duties for providers and deployers.
F
Framework comparison
A side-by-side view of the main AI rules by type, scope and whether they can be certified, as of October 2026.
G
General-purpose AI model obligations
Duties for providers of models that can do many tasks: technical documentation, information for downstream builders, a copyright policy and a public training content summary.
I
ISO/IEC 42001
The international standard (December 2023) for an AI management system: policies, roles, risk and impact assessment, Annex A controls, internal audit and improvement.
M
Model registry
A store of model versions with training data reference, code version, parameters, evaluation results, approver and stage (staging, production, archived).
N
NIST AI RMF
A free, voluntary US framework (version 1.0, January 2023, under revision as of 2026) with four functions: Govern, Map, Measure and Manage.
O
OECD AI Principles
The first intergovernmental AI standard, adopted 2019 and updated May 2024: five values (inclusive growth, human rights and fairness, transparency, robustness and safety, accountability) and five recommendations for governments.
P
Pakistan and India AI policies
Pakistan's National AI Policy 2025 (cabinet approval July 2025) focuses on adoption, skills and a secure AI ecosystem.
Prohibited AI practices
Uses banned since 2 February 2025, such as harmful manipulation, exploiting vulnerabilities, social scoring, crime prediction from profiling alone, untargeted facial scraping, emotion recognition at work or school, and sensitive biometric categorisation.
Provider and deployer
Under the EU AI Act, the provider develops a system or model and places it on the market under its name; the deployer uses it under its authority.
R
Risk tiering
Assigning each system an internal tier, often low, medium or high, from its impact on people and how much a human checks its output, alongside its legal tier.
S
Shadow AI
AI that staff use without the organisation knowing or approving: public chatbots, personal API keys in scripts, AI browser extensions.
System classification
Describing an AI system by purpose, users, affected people, decisions supported, data, model and deployment, then labelling its type and legal category.
System owner
The named person accountable for an AI system's behaviour, changes and residual risk, usually supported by a technical owner who runs it day to day.
T
Third-party AI
AI that arrives through vendors: API models, AI features inside SaaS products and open models you download.
U
UAE and Saudi AI principles
The UAE Charter for the Development and Use of AI sets twelve principles, including safety, algorithmic bias, privacy, transparency and human oversight.
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