arXiv:2605.12729v2 Announce Type: replace-cross Abstract: 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. This is crucial because operational decision
The paper signals the increasing maturity and application of large language models from general-purpose assistants to highly specialized and autonomous operational roles in critical IT infrastructure.
This development indicates a nearing inflection point where AI can autonomously manage complex network and IT operations, significantly impacting efficiency and the future of white-collar IT work.
The shift from human-supervised IT operations to agent-based, AI-driven systems is accelerating, demanding new architectures, evaluation methods, and safety protocols for critical infrastructure.
- · AI software developers
- · Cloud service providers
- · Large enterprises
- · IT automation vendors
- · Entry-level IT operations staff
- · Legacy IT management solutions
- · Companies slow to adopt AI
Increased efficiency and reduced human error in network and IT operations.
Significant displacement of human labor in IT management and support roles, leading to reskilling demands.
Potential national security implications if such autonomous AI systems become targets for sophisticated cyberattacks.
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Read at arXiv cs.AI