Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G

Computer Science > Artificial Intelligence [Submitted on 20 May 2026] Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G Liang Wu, Kelly Wan, Mayank Darbari, Liangjie Hong The proliferation of emerging applications, such as autonomous driving and immersive experiences, demands cellular networks that are not only faster, but fundamentally more resilient and autonomous. This paper presents a BlueSky vision on how Artificial Intelligence will be natively integrated into 6G, shifting the paradigm from \underline{Network for AI} to \underline{AI for Network}. We envision that, unlike 5G's reliance on scattered, ad-hoc models each trained for a single task, native AI in the 6G era will be anchored by a foundation model and and orchestrated via collaborative multi-agent systems, framing network management as a unified, multi-modal, multi-task optimization problem. Built on this vision, we outline two transformative directions. The first focuses on developing a 6G foundation model as a unified backbone, with task-specific knowledge distilled into compact models suited for diverse edge deployments. The second advances multi-agent systems designed to autonomously diagnose, maintain, and recover networks with minimal human intervention. These directions chart a roadmap for 6G to evolve into an intelligent, self-sustaining communication infrastructure. Comments: Accepted at KDD 2026 Subjects: Artificial Intelligence (cs.AI); Machine Learning (cs.LG) MSC classes: I.2.11, C.2.1 Cite as: arXiv:2605.21395 [cs.AI]   (or arXiv:2605.21395v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2605.21395 Focus to learn more Submission history From: Liang Wu [view email] [v1] Wed, 20 May 2026 16:53:06 UTC (69 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-05 Change to browse by: cs cs.LG References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)