{"id":46802,"date":"2026-06-17T16:54:12","date_gmt":"2026-06-17T15:54:12","guid":{"rendered":"https:\/\/www.gsma.com\/solutions-and-impact\/technologies\/networks\/?post_type=gsma_theme_resources&p=46802"},"modified":"2026-06-17T16:54:30","modified_gmt":"2026-06-17T15:54:30","slug":"agentic-network-for-mobile-ai-era","status":"publish","type":"gsma_theme_resources","link":"https:\/\/www.gsma.com\/solutions-and-impact\/technologies\/networks\/gsma_resources\/agentic-network-for-mobile-ai-era\/","title":{"rendered":"Agentic Network for Mobile AI Era"},"content":{"rendered":"\n
\n
Download report<\/a><\/div>\n<\/div>\n\n\n\n
<\/div>\n\n\n\n

In recent years, the rapid development of artificial intelligence (AI) technologies has not only given rise to new business models but also posed profound challenges to the operation and management (O&M) of global network infrastructure. The synergy of 5G-Advanced (5G-A) and AI lies at the heart of today’s digital transformation. On the one hand, “Network for AI” requires the network itself to become an efficient platform to enable AI services. Emerging AI services, such as immersive interaction like extended reality (XR), pose stringent requirements on network bandwidth, latency, and reliability.<\/p>\n\n\n\n

Facing increasingly severe energy efficiency management in traditional network operations, new services’ requirements for deterministic Service Level Agreements (SLAs), and mounting O&M difficulties caused by exponential growth of network complexity, leading global operators are actively looking to \u201cAI for Network\u201d to address these challenges by introducing AI agents into service creation and O&M processes. Mobile networks are now evolving towards multiple agent-based networks. Currently, on the network side, \u201cAI for Network\u201d focuses on four high-value scenarios:<\/p>\n\n\n\n

    \n
  • AI for network maintenance<\/strong>: AI is used to reduce network downtime, reduce O&M manpower requirements, and improve network O&M efficiency.<\/li>\n\n\n\n
  • AI for network optimization: AI is used to dynamically adjust network parameters to achieve optimal overall network performance, continuously improving network quality.<\/li>\n\n\n\n
  • AI for network service assurance: AI is used to support differentiated services experience assurance and agile operations.<\/li>\n\n\n\n
  • AI for network energy saving: AI enables maximum energy saving while maintaining network performance.<\/li>\n<\/ul>\n\n\n\n

    The convergence and innovation of AI technologies with 5G-A and future networks are driving mobile networks to evolve from automation to intelligence and is reshaping the following aspects of mobile networks:<\/p>\n\n\n\n

      \n
    • Interaction Reshaping<\/strong>: Shift from traditional command-line O&M interaction to more intuitive dialog interaction, optimizing the O&M engineer experience and operation efficiency.<\/li>\n\n\n\n
    • Capability Remodeling<\/strong>: Shift from independent operation of a single domain e.g., RAN, to integrated collaboration across multiple domains, e.g., RAN & CN, improving the overall utilization of network resources.<\/li>\n\n\n\n
    • Process Restructuring<\/strong>: Shift from passive response to proactive awareness and prediction, achieving intelligent upgrades to O&M processes.<\/li>\n<\/ul>\n\n\n\n
      <\/div>\n\n\n\n

      Complete the form below and download the whitepaper<\/h2>\n\n\n