{
  "id": 4432,
  "url": "https://arxiv.org/abs/2605.12729v2",
  "title": "Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety",
  "summary": "Large language models are increasingly being used to support network operations (NetOps) and artificial intelligence for IT operations (AIOps), including incident investigation, root-cause analysis, configuration synthesis, and limited self-healing. In both NetOps and AIOps, this shift is changing how tasks are managed. Agent-based operations work as workflows, from gathering evidence to taking action, following permissions, policies, and checks, and providing rollback options when necessary. Th",
  "authors": "Muhammad Bilal, Jon Crowcroft, Ruizhi Wang, Xiaolong Xu, Schahram Dustdar",
  "category": "research",
  "topics": "agents-autonomy,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-12T20:31:41.000Z",
  "fetched_at": "2026-07-14T16:30:59.237Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4432",
  "original_url": "https://arxiv.org/abs/2605.12729v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}