AI Agent Use Cases and Requirements in 6G Network
draft-yu-ai-agent-use-cases-in-6g-01

Network Working Group                                              M. Yu
Internet-Draft                                                   A. Wang
Intended status: Informational                                     J. Li
Expires: 8 January 2026                                            Z. Li
                                                           China Telecom
                                                             7 July 2025

           AI Agent Use Cases and Requirements in 6G Network
                  draft-yu-ai-agent-use-cases-in-6g-01

Abstract

   This draft introduces use cases related to AI Agents in 6G networks,
   primarily referencing the technical report of 3GPP SA1 R20 Study on
   6G Use Cases and Service Requirements (TR 22.870).  It also
   elaborates on some of the requirements for introducing AI Agents into
   6G networks from the perspective of operators.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . .   3
     2.1.  Novel Intelligent 6G Services Enabled by Network AI
           Agents  . . . . . . . . . . . . . . . . . . . . . . . . .   4
       2.1.1.  Use Case On 6G Network Providing On-demand Networking
               with AI Agent . . . . . . . . . . . . . . . . . . . .   4
       2.1.2.  Use Case On Intelligent Calling Services  . . . . . .   4
       2.1.3.  Use Case On Disaster Rescue Planning Enabled By Network
               AI Agents . . . . . . . . . . . . . . . . . . . . . .   5
     2.2.  Device-Network Collaboration  . . . . . . . . . . . . . .   5
       2.2.1.  Use Case On 6G System Assisted AI Agent Service . . .   5
       2.2.2.  Use Case On Smart Housekeeping  . . . . . . . . . . .   6
       2.2.3.  Use Case On Child Health Management Assistant . . . .   6
     2.3.  Multiple Devices Collaboration  . . . . . . . . . . . . .   6
       2.3.1.  Use Case On Collaborative AI Agents . . . . . . . . .   7
       2.3.2.  Use Case On AI Agents Communication . . . . . . . . .   7
     2.4.  Network-Application Collaboration . . . . . . . . . . . .   7
       2.4.1.  Use Case On Intelligent Communication Assistant . . .   7
       2.4.2.  Use Case On 6G AI Agents Collaboration With Third-party
               AI Using LLM  . . . . . . . . . . . . . . . . . . . .   8
   3.  Potential Requirements for 6G Network . . . . . . . . . . . .   8
     3.1.  The Identity of AI Agents . . . . . . . . . . . . . . . .   8
     3.2.  Efficient Collaboration . . . . . . . . . . . . . . . . .   8
     3.3.  Registration and Discovery  . . . . . . . . . . . . . . .   9
     3.4.  Service and Data Exposure . . . . . . . . . . . . . . . .   9
     3.5.  Reliability Assurance . . . . . . . . . . . . . . . . . .   9
     3.6.  High-performance Communication  . . . . . . . . . . . . .   9
     3.7.  Security  . . . . . . . . . . . . . . . . . . . . . . . .   9
     3.8.  Energy Efficiency . . . . . . . . . . . . . . . . . . . .   9
   4.  Conclusion  . . . . . . . . . . . . . . . . . . . . . . . . .  10
   5.  Informative References  . . . . . . . . . . . . . . . . . . .  10
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  10

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1.  Introduction

   Currently, with breakthroughs in large language models and multimodal
   technologies, AI Agent has emerged as a major research focus in the
   industry.  Equipped with capabilities such as intent understanding,
   action planning, decision-making, task execution, and self-awareness,
   AI Agents can integrate environmental perception, memory, tool
   invocation, and multi-agent collaboration to accomplish complex
   tasks.  They have already demonstrated significant value in key
   fields like autonomous driving, intelligent customer service, and
   smart home systems.  In the 6G era, the introduction of AI Agent
   technology will enable operators to fully leverage the potential of
   mobile communication networks, significantly improving network
   operational efficiency and user experience.  As a result, AI Agents
   are expected to become a key research focus in future 6G networks,
   leading to deep integration between 6G and AI Agent technologies.

   In the 3GPP R20 standardization research for 6G, AI Agent has been
   one of the most discussed and debated topics, whether in SA1's study
   on 6G scenarios and requirements or SA2's research on network
   architecture.  In the SA1#109 meeting, 19 contributions related to AI
   Agents were submitted, which include 16 new use cases, with 4 use
   cases ultimately agreed.  And a preliminary definition of AI Agent
   from a capability perspective was adopted: "an automated intelligent
   entity capable of e.g interacting with its environment, acquiring
   contextual information, reasoning, self-learning, decision-making,
   executing tasks (autonomously or in collaboration with other Al
   Agents) to achieve a specific goal."  In the SA1#110 meeting, more
   than 30 contributions related to AI Agents were submitted, which
   include 22 new use cases, with 7 ultimately agreed.

   This draft summarizes and categorizes the AI Agent-related use cases
   in 6G networks, with a brief introduction provided in Section 2.  In
   Section 3, from an operator's perspective, we elaborate on the
   potential requirements for introducing AI Agents into 6G networks,
   which should be considered when designing the A2A protocol in mobile
   communication network.  In Section 4, we conclude this draft.

2.  Use Cases

   AI Agents can be deployed at various locations within the 6G system.
   Depending on their deployment positions, AI Agents in 6G can be
   classified into On-device AI Agents (deployed on user devices),
   application AI Agents, network AI Agents (deployed within the future
   6G network), operation management AI Agents, etc.  For instance,
   terminal AI Agents refer to those implemented on end-user devices,
   while network AI Agents are those embedded within the 6G network.

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   This section summarizes and categorizes AI Agent-related use cases in
   6G networks.  Unlike AI Agents in the internet domain, use cases
   involving AI Agents in mobile communication networks place greater
   emphasis on how network AI Agents can deliver 6G services to users,
   as well as how different AI Agents within the 6G system coordinate
   with each other.

2.1.  Novel Intelligent 6G Services Enabled by Network AI Agents

   By deploying AI Agents within 6G network, the 6G network can provide
   users with novel intelligent services.  These intelligent services
   may represent combinations of multiple network capabilities, such as
   communication services, sensing services, AI/ML services, computing
   services, and more.  Users only need to express their intent to the
   6G network, without requiring specialized technical knowledge to
   decompose the intent into technical requirements.  In this context,
   3GPP SA1 has formally defined network intent as: Expectations
   including requirements, goals and constraints without specifying how
   to achieve them.

2.1.1.  Use Case On 6G Network Providing On-demand Networking with AI
        Agent

   User Harry owns a smart robot named Ron and has a lovely pet dog
   called Bob. Bob needs to be walked twice daily.  While away on a
   business trip, Harry sends his request through an operator portal
   (which could be an app, a mobile webpage, etc.) to the 6G network's
   AI Agent, expressing his intention for robot Ron to ensure Bob's
   safety during walks.  The network AI Agent processes this request,
   determines that the task requires perception services and QoS-
   guaranteed services, and then distributes these services to the
   relevant network entities.

2.1.2.  Use Case On Intelligent Calling Services

   The network delivers AI Agents enabled intelligent calling services
   that revolutionize traditional voice communications.  By integrating
   recognition and perception capabilities of AI Agents, it offers two
   key functionalities: 24/7 Intelligent Answering (handling calls
   during unreachability, e.g., flight/power-off modes with contextual
   responses) and Intelligent Answering Machine (managing calls during
   user unavailability, e.g., meetings, with call logging).  These
   services operate under strict user authorization, allowing
   customization of voice tones, trigger conditions (e.g., flight mode
   activation), and data permissions (call records/summaries).  For
   instance, when a subscriber enables the service, the network
   autonomously answers calls based on predefined preferences and
   provides post-call analytics.

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2.1.3.  Use Case On Disaster Rescue Planning Enabled By Network AI
        Agents

   When a disaster strikes, unpredictable challenges such as collapsed
   buildings, deformed roads, and communication outages make the rescue
   extremely complex.  By leveraging 6G network AI Agents for rescue
   planning, the rescue efficiency can be significantly improved,
   maximizing the protection of victims‘ lives and personal property.
   In this case, the intent may be “execute the rescue mission with
   multiple rescue robots in a certain area”. Upon receiving the intent,
   the network AI agents initiate the rescue planning and decompose the
   rescue into multiple operations and other standardized 3GPP service.
   This may specifically include: road obstacle sensing (sensing
   service), multi-robot rescue route planning (AI inference service),
   training obstacle avoidance models (AI training service), real-time
   optimal route computation for rescue robots (computing service) and
   communication resource allocation for disaster zones (communication
   service).

2.2.  Device-Network Collaboration

   With the rapid advancement of technologies like smartphones and
   lightweight large-scale AI models, capabilities of user devices have
   significantly expanded, enabling autonomous execution of certain AI
   tasks and independent decision-making.  However, due to inherent
   device limitations - including constrained computational resources
   and battery capacity - deploying complex AI agents or performing
   sophisticated AI tasks locally on devices remains challenging.
   Consequently, investigating optimal collaboration mechanisms between
   UE-based AI agents and network-based AI agents to accomplish complex
   tasks represents a critical research direction for 6G networks.

2.2.1.  Use Case On 6G System Assisted AI Agent Service

   AI-powered devices can interact with their environment—collecting
   data, making autonomous decisions, and executing actions.  The 6G
   system will enhance AI agents by providing supplementary
   environmental data (e.g., real-time sensing for traffic awareness)
   and dynamic QoS updates for adaptive decision-making.Additionally, 6G
   must support secure AI agent authentication and inter-agent
   communication, as traditional identifiers like SUPI/IMSI may not
   suffice for dynamic AI functionalities.  The rise of AI agents will
   also increase "horizontal traffic" between devices, enabling
   collaboration within agent groups and with third-party applications.

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2.2.2.  Use Case On Smart Housekeeping

   6G system could help to keep the family daily care and security,
   requiring advanced automation and management capabilities to maintain
   a comfortable and efficient living space.  There will be more AI
   related applications and intelligent devices (e.g. robots, UAVs,
   autonomous vehicles) in the 6G era.  Users will be able to express
   their requirements through natural language to convey their needs.
   In certain scenarios, multiple devices will need to collaborate to
   complete complex tasks.  The 6G system can dynamically coordinate
   devices based on user's supply and demand requirements.

2.2.3.  Use Case On Child Health Management Assistant

   Lily's smartwatch AI agent continuously tracks her vital signs (heart
   rate, body temperature) during school hours.  When detecting abnormal
   readings (elevated heart rate and temperature), the system
   automatically escalates monitoring frequency and initiates an
   emergency protocol by: (1) verifying authorization through the
   network, (2) selecting the optimal emergency contact (mother Emma,
   based on real-time proximity and availability data), and (3)
   coordinating with Emma's AI agent by sharing Lily's health metrics,
   location data, and environmental conditions.  The network facilitates
   this process by providing positioning services, environmental sensing
   data, and secure data transmission between authorized AI agents.
   Emma's AI agent then calculates the fastest route to Lily's location
   while receiving continuous health updates, enabling prompt medical
   intervention.  This scenario showcases the seamless integration of
   UE-based and network-based AI capabilities, including cross-domain
   data analysis, dynamic service invocation, and privacy-preserving
   emergency response mechanisms, ultimately delivering timely
   healthcare intervention while maintaining strict data security
   protocols.

2.3.  Multiple Devices Collaboration

   Under the powerful communication capabilities of 6G networks,
   multiple on-device AI Agents can collaborate with each other to
   accomplish complex AI tasks.  These AI Agents may from either the
   same application or different applications.

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2.3.1.  Use Case On Collaborative AI Agents

   John and Ann's electric vehicle (EV) uses an AI Agent to optimize
   charging based on dynamic energy prices and travel plans.  While John
   sleeps during a business trip, his EV's AI Agent detects high
   electricity prices at the hotel location and considers selling
   battery power back to the grid.  To verify feasibility, it securely
   accesses both John and Ann's calendar AI Agents (hosted by different
   providers) without waking them.  Learning of John's planned 900km
   return trip, the AI Agent cancels the energy sale.  All cross-border
   data exchanges maintain strict privacy, blocking unauthorized access
   (e.g., from friends' AI Agents).  This demonstrates how standardized
   AI Agent interoperability enables intelligent, user-authorized
   decisions across distributed systems.

2.3.2.  Use Case On AI Agents Communication

   A group could be established for users and their AI agents to
   communicate with each other.  To complete a complex task involving
   multiple users and triggered by a user, AI agent or application,
   communication domain for multiple groups could be established,
   Communication domain could be dynamically created for users and AI
   agents from multiple groups to communicate with each other for a
   specific task during a specific time.  Only the AI agents in the same
   domain can communicate with each other.  If authenticated /
   authorized, users and AI agents could join this group via various
   access technologies, including the cellular network, WiFi and
   Ethernet, etc.

2.4.  Network-Application Collaboration

   The 6G network AI Agents and application AI Agents can fully
   collaborate to accomplish network tasks.  On one hand, AI agents
   within the 6G network can invoke appropriate application AI Agents
   based on service characteristics.  On the other hand, the network AI
   Agents can share network data and domain expertise with application
   AI Agents, providing crucial data support for application AI Agents.

2.4.1.  Use Case On Intelligent Communication Assistant

   Currently, most of the personal AI assistants are provided on the
   devices (e.g. smart phones).  However, the limitation of the power
   and thermal factors are the bottlenecks of the AI assistant
   development on devices.  Operators are highly possible to provide the
   Intelligent Communication Assistant services leveraging 6G network AI
   Agents.  For example, Alice is a business traveler, and her personal
   assistant in 6G network automatically monitors flight status, books a
   taxi upon landing by interfacing with the taxi company's registered

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   AI service, and guides her to the vehicle using real-time location
   data - all without taxing her smartphone's resources.  This includes
   collaboration with AI Agents for applications such as taxi booking
   and real-time navigation.

2.4.2.  Use Case On 6G AI Agents Collaboration With Third-party AI Using
        LLM

   A 3rd party application (e.g. a smart city traffic management system)
   AI Agent sends a text-based request or query to the 6G network.  The
   request is processed by an AI agent in the 6G network that leverages
   LLMs and the network's advanced capabilities (e.g.  sensing, real-
   time data processing, telemetry, analytics, and others) to provide a
   response or perform an action.  The 6G network AI agent acts as an
   intelligent intermediary, interpreting the text-based request,
   gathering necessary data, and returning a response or executing a
   task.

3.  Potential Requirements for 6G Network

   In this section, we present potential requirements to 6G network that
   may arise from the introduction of AI Agents in 6G mobile
   communication networks from an operator's perspective.  Some of these
   potential requirements have already been agreed by 3GPP, while others
   have not yet been adopted by 3GPP.

3.1.  The Identity of AI Agents

   The 6G network shall support secure authentication, authorization,
   and management mechanisms for AI Agents' digital identities.  These
   AI Agents include on-device AI Agents, 3rd party AI Agents, network
   AI Agents, etc.  A robust identity management mechanism is the
   prerequisite for interactions between users and AI Agents, as well as
   between different AI Agents.

3.2.  Efficient Collaboration

   The 6G network shall support efficient collaboration between
   different AI Agents and between AI Agents and the tools.  This
   include: developing agent communication protocols better suited for
   6G network characteristics, supporting multimodal data (such as text,
   audio, video, etc.) interactions, enabling rapid transmission of
   massive data volumes, etc.

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3.3.  Registration and Discovery

   The 6G network shall support mechanisms for on-device AI Agents, 3rd
   party AI Agent, network AI Agents and tools to register their
   attributes to 6G network, which enables efficient, cross-platforms
   and cross-domain AI Agents and tools discovery.  This may different
   from the discovery mechanism in A2A protocol (e.g. NRF discovery
   mechanism).

3.4.  Service and Data Exposure

   The 6G network shall support secure mechanisms to expose the 6G
   services (e.g. sensing service, computing service, AI/ML service,
   etc.) and network data (e.g. sensing data, positioning data, etc.) to
   3rd party AI Agents.

3.5.  Reliability Assurance

   The 6G network shall be able to provide mechanisms (e.g. network
   digital twin) to ensure the reliability and the validity of the
   decisions made by the AI Agents.  The decisions made by the AI Agents
   in 6G network may directly change the network status, parameters,
   configurations.  Only decisions that have been verified for
   reliability can be executed to change the network environment.

3.6.  High-performance Communication

   The 6G network shall enable high-performance communication, which may
   include low latency, high band-width, ultra-high data rate, etc.
   This is crucial for numerous scenarios such as device-network
   collaboration, network-application collaboration.

3.7.  Security

   The security of AI Agents communication in 6G includes the data
   protection and user consent.  Data pravacy means tha 6G networks
   shall support end-to-end encryption for the interactions between AI
   Agents to ensure robust data protection and privacy security for
   sensitive information.  Besides, 6G network shall be able to provide
   mechanisms to collect the user consent for the local data collection.

3.8.  Energy Efficiency

   The 6G network shall be able to provide mechanisms to optimize the
   communication between AI Agents (especially for the on-device AI
   Agents) to reduce energy consumption.

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4.  Conclusion

   AI Agents are expected to represent a critical innovation vector for
   6G.  This draft explores the transformative potential of AI Agents in
   6G networks, outlining key use cases and operational requirements
   from an operator’s perspective.  When designing A2A protocols for 6G
   networks, the aforementioned requirements should be thoroughly
   considered and incorporated into the protocol architecture.

5.  Informative References

   [TR_22.870]
              "3GPP TR 22.870, "Study on 6G Use Cases and Service
              Requirements", 2025.".

Authors' Addresses

   Menghan Yu
   China Telecom
   Beiqijia Town, Changping District
   Beijing
   Beijing, 102209
   China
   Email: yumh1@chinatelecom.cn

   Aijun Wang
   China Telecom
   Beiqijia Town, Changping District
   Beijing
   Beijing, 102209
   China
   Email: wangaj3@chinatelecom.cn

   Jinyan Li
   China Telecom
   Beiqijia Town, Changping District
   Beijing
   Beijing, 102209
   China
   Email: lijinyan@chinatelecom.cn

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   Zhen Li
   China Telecom
   Beiqijia Town, Changping District
   Beijing
   Beijing, 102209
   China
   Email: liz779@chinatelecom.cn

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