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Standards Database

Find information on AI-related standards using the search and filtering capabilities below. This database currently covers nearly 300 relevant standards that are being developed or have been published by a range of prominent Standards Development Organisations.

Hover over the filter categories here to learn more about them:

Domain The industry or sector that the standard covers (e.g. Energy).

Type of standard Whether the standard covers terminology, processes, performance requirements or measurement requirements.
Application The type of technology, method or application covered by the standard. (E.g. Natural language processing)

Stage of development If the standards is pre-draft, draft or published.
Scope Whether the standard is focused entirely on AI, or is adjacent to AI.

Issuing body The standards body or organisation that issued the standard.
Topic The theme, principle or area covered by the standard (e.g. bias and discrimination).

Committee The standards committee that developed this standard.
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This Recommendation provides a framework for artificial intelligence (AI) enhanced telecom operation and management (AITOM). It describes the functional framework of AITOM to support telecom operation management for efficiency improvement, quality assurance, cost management, and security assurance. It also describes…
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Standards Body: ITU
Last updated: 7 Jan 2025
Recommendation ITU-T Y.3183 provides a framework for machine learning-assisted network slicing management, leveraging vertical end users’ feedback on quality of experience (QoE), which can help achieve the runtime optimization of user perceived performance. The overall architecture, components, workflow and related…
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Standards Body: ITU
Last updated: 7 Jan 2025
Recommendation ITU-T Y.3173 specifies a framework for evaluating the intelligence of future networks including IMT-2020 and a method for evaluating the intelligence levels of future networks including IMT-2020 is introduced. An architectural view for evaluating network intelligence levels is also…
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Standards Body: ITU
Last updated: 7 Jan 2025
This Recommendation provides a framework for data handling to enable machine learning (ML) in future networks including International Mobile Telecommunications (IMT)-2020. The scope of this Recommendation includes: – background and motivations; – high-level requirements of data handling and data models…
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Standards Body: ITU
Last updated: 7 Jan 2025
This Recommendation1 specifies a framework in the form of constraints, performance criteria and methods for the development of intrusive parametric, machine learning (ML) based models for the assessment of transmission network impact on speech quality for mobile packet-switched voice services.…
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Standards Body: ITU
Last updated: 7 Jan 2025
This document establishes an Artificial Intelligence (AI) and Machine Learning (ML) framework for describing a generic AI system using ML technology. The framework describes the system components and their functions in the AI ecosystem. This document is applicable to all…
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This Recommendation presents an overview of the framework for a language learning system based on speech and natural language processing (NLP) technology. It describes the features, general requirements and functionality, which is a framework to support language-learning systems. The scope…
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Standards Body: ITU
Last updated: 7 Jan 2025
This Recommendation provides a framework of civilian unmanned aerial vehicle flight control using artificial intelligence (AI), including the flight navigation control of a civilian unmanned aerial vehicle (CUAV) and the specific flight control according to the vertical industry application requirements.…
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Standards Body: ITU
Last updated: 7 Jan 2025
This document provides a reference of 42 knowledge units as required and applied in the Information and Communication Technology (ICT) professional work environment that can be understood across Europe. An intrinsic link with the EN 16234‑1 (e-CF) is an essential…
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Standards Body: BSI
Last updated: 7 Jan 2025
The document will establish requirements and recommendations for face- aware systems, which: capture images automatically and semiautomatically; capture (output) images that target application specific quality related requirements; support the capture of face images that are suitable for automated face recognition;…
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The WI will provide terms and definitions used within the scope of the ISG ENI, in order to achieve a ‘common language’ across all the ISG ENI documentation. Ā© Copyright 2022, ETSI
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Standards Body: ETSI
Last updated: 7 Jan 2025
The purpose of this work item is to draft a GS to define the software functional architecture of ENI. This includes: – defining the software functions and interactions that satisfy the ENI Requirements – defining a software architecture, in terms…
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Standards Body: ETSI
Last updated: 7 Jan 2025
The present document will describe the motivation, requirements, and challenges of using flow-oriented on-path telemetry techniques which provides relevant measurement or event reports to the AI-enabled network entities. The present document will outline a reference framework, named as “In-situ Flow…
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Standards Body: ETSI
Last updated: 7 Jan 2025
This Work Item specifies a framework for use within ETSI ENI ISG to coordinate and promote public demonstrations of Proof of Concept (PoC) validating key technical components developed in ENI. The objective for the PoCs is to build commercial awareness…
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Standards Body: ETSI
Last updated: 7 Jan 2025