AI Ops is a natural fit in the 5G era with software-defined networks that are increasingly programmable. Human supervision of 5G networks is a bit like trying to hop onto an electric train after it has left the station. AI-assisted automation is the holy grail for network managers rattled by a catastrophe precipitated by human errors. While early trials of AI Ops in private and public 5G networks are promising, data capture in network labyrinths is forbidding due to many silos, emergent data standards, and insufficient data to train AI models. How are telcos and enterprise CIOs balancing the risk and benefits of autonomous networks steered by AI? Let’s find out!
Our guest for the podcast is Aaron Boasman-Patel, Vice President of AI & Customer Experience at TM Forum. He is responsible for defining and executing the strategic vision for all AI, manages the cross-ecosystem collaboration projects, and helps to set industry standards.
In our discussion today, we will uncover a few things, such as:
- What are the early lessons from experimenting with autonomous networks?
- What are the challenges of setting data standards for AI Operations and automation?
- How does AI Ops benefit private 5G deployments? and
- How do CIOs prepare for autonomous networks and avoid errors without a way to learn from past mistakes?
So, let us welcome Aaron Boasman-Patel.
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