Self-Driving Networks: AI Automation for Enterprise IT

Abstract

The pressure to manage enterprise networks has never been greater than it is today. The rise of artificial intelligence workloads, the explosion of IoT devices, multi-cloud computing and a dispersed workforce model have created environments that are too complex to manage. In this article we explore the rise of self-driving networks as an organisational and strategic response to this phenomenon. The article builds on the confluence of developments in AIOps, agentic automation, high-performance network hardware design and built-in security to offer a five-point maturity model for network autonomy, a high-level overview of the key architectural building blocks that support self-driving capability, and recommendations for organisations at various points in the transition. The discussion includes the evolution of network management, the distinct features that distinguish self-driving networks from previous generations of automation, the state of the art, industry applications, and the challenges of transition. The article concludes that the enabling components of autonomy are readily available and tested today, and that organizations that begin the structured journey to autonomy now will stand a much stronger chance of competing, securing and scaling AI-powered operations in the future.