Standard20262026-08-293GPP SA6 Study Item (SID under preparation, work plan Aug-Nov 2026)3GPP6Gapplication-enablementagent标准
SA6 study analysing 6G use cases (per SA1 TR 22.870, including third-party AI agent collaboration) to derive application-enabler level requirements and shape 6G application enablement aligned with the IMT-2030 vision and industry initiatives (GSMA Open Gateway, ETSI OpenCAPIF). Work plan: SA6#68 (Aug 25-29) proposals, moderated discussions Sep/Oct, SA6#70 (Nov 17-21), then SID submission to SA plenary. Output TR 23.xxx will form the basis for normative 6G application enablement work. SID draft: S6-255552 (3GPP FTP; accessible via browser, scripted download returns 403).
Standard20262026-03-013GPP Technical Report (approved at TSG SA#111, March 2026)3GPP6Gagent需求标准
Stage-1 6G study approved in March 2026 with 200+ use cases, explicitly including "6G AI agent collaboration with third-party AI" as a use case family and requirements such as exposing services to authorised third-party AI agents. TR 22.870 frames AI agents as automated intelligent entities capable of intent understanding, contextual reasoning, self-learning and collaborative decision-making within the 6G system. Anchor reference for Release 21 normative work together with TR 38.914.
CAAM proposes a contextual authorization mesh for agents: authorization decisions are bound to invocation context rather than long-lived static tokens, limiting over-broad delegation in agentic systems.
Individual draft enumerating architectural requirements for supporting AI agents on the Internet: how agents are addressed, identified, discovered and how their capabilities are described within existing Internet architecture.
An individual IETF draft proposing a two-phase addressing scheme and a three-dimension framework for agent identification and addressing on IPv6 networks.
SAIP defines a signed agent identity protocol that cryptographically attests an agent's identity, answering how a peer can prove it is the agent it claims to be.
Defines the Agent Registration and Discovery Protocol: how an agent registers itself, declares its capabilities and endpoints, and how other agents or gateways locate it.
Specifies trust, identity and verifiable provenance mechanisms for agent-to-agent interaction, enabling participants to authenticate counterparts and audit what an agent actually did.
Proposes an architecture combining network digital twins with agentic AI for AI-driven network operations, using the twin as a safe substrate for agent reasoning about the production network.
Defines a gateway-managed capability-directory framework for the Internet of Agents: a control-plane function maintaining validated capability information beyond transient advertisements, static endpoint bindings or external descriptions, with requirements and a common object model.
Standard20262026-06-09ITU-T SG13 work item (under study)ITU-Tagentagent-as-a-service标准
SG13 Q17/13 work item on requirements for AI Agent as a Service (Y.aias-reqts), with 2026-06 contributions from ETRI covering proposed revisions of scope/overview of AI agent and text for AI agent as a service in clause 6.2. Related parallel SG13 items: Y.AMLM-reqts (ML model adaptation), Y.MLPaaS-reqts (ML PaaS). Signifies that agent-as-a-service is entering requirements-stage standardization at ITU-T.
SG13 technical report under study defining the AI-agent communication network (ACN) in IMT-2020 networks and beyond. Presented among SG13 AI-agent achievements alongside YSTR.NAC and Y.IMT2020-DIC; echoes the ACN concept promoted by China Mobile at the 2026 Cloud-Network Intelligence Conference. Note: China Mobile's CN indicator and ITU-T ACN terminology converge on the same problem space — agent-native networking for 6G.
SG13 Q22/13 technical report (target 2026-11) surveying standardization status and roadmap for networking that supports AI agent collaboration across heterogeneous organizations, protocols and data formats; collects related Recommendations and TRs and proposes standardization directions. Companion item: YSTR.NAC (Framework of networking for AI agent collaboration in future networks). Supported by China Telecom, CAICT, China Unicom, BUPT, Zhejiang Lab and NICT; editors include Jingwen LI and Ved P. KAFLE.
RFC 10038 specifies distribution of the Segment Routing over IPv6 (SRv6) locator via DHCPv6, automating locator provisioning and removing a major operational friction in large-scale SRv6 deployments.
Published 2026-03-02, effective 2026-06-01 (project 2025-CCSA-002, TC1/WG1). Defines the capability classification method for AI agent systems and the technical requirements per level; applicable to both agent providers and consumers for grading agent systems. One of 75 group standards approved in the same batch.
A benchmark of 369 real tasks across real operating systems (Ubuntu/Windows/macOS), requiring agents to control GUIs like a human to complete open-ended computer tasks.
Shows that designing the interface through which agents interact with codebases (Agent-Computer Interface) dramatically improves autonomous bug fixing on real GitHub issues.
A benchmark of 466 questions requiring reasoning, multimodal handling, web browsing and tool use — questions simple for humans yet hard for state-of-the-art AI.
The Stanford "Smallville" experiment: 25 LLM agents with memory, reflection and planning living in a simulated town, a landmark in agent society research.
Encodes Standardized Operating Procedures into LLM agent roles, assembling a software company simulation that turns one-line requirements into working programs.