Lumen’s Journey to Self-Driving Networks
As AI reshapes the fabric of digital infrastructure, network leaders are redefining how scale, reliability, and intelligence coexist. In this session from Selector’s AI Summit for Network Leaders, Greg Freeman, Vice President of Network Customer Transformation at Lumen Technologies, shares the five-year transformation journey that turned one of the world’s largest networks into a self-healing, AI-driven system.
Drawing from deep operational experience, Greg unpacks how Lumen inverted its support model, moved from manual intervention to closed-loop orchestration with Itential, and began applying agentic AI to predict, act, and communicate in real time. The result is a pragmatic blueprint for evolving from task automation to intelligent infrastructure – one that’s measurable, repeatable, and built to scale in the AI era.
We wanted orchestration. We knew that to get to closed-loop, no human touch, we needed orchestration.
Greg Freeman, Vice President Network and Customer Transformation at Lumen
Key Takeaways for Infrastructure Leaders
- Understand why the next era of automation is about autonomy and how AI enables self-driving operations at scale.
- See what it takes to redesign network operations so most activity happens machine to machine while engineers focus on innovation.
- Learn how to turn clean, contextual data into actionable intelligence that prevents problems before they occur.
- Explore how orchestration delivers measurable business outcomes while keeping automation safe and auditable.
- Discover how to apply machine learning, generative, and agentic AI together to predict, explain, and act in real time.
- Learn how Model Context Protocol (MCP) connects tools and agents securely across distributed systems.
- Understand what new skills – Python, Ansible, and workflow design, prepare teams to operate in an AI-driven environment.
- See how to prove automation value quickly with small, high-impact workflows that reduce manual touches and downtime.
- Discover why pragmatic leadership and iterative change are the keys to sustainable AI transformation in infrastructure.
