AI for Networking: Agentic AI Powering Intelligent Automation
Organizations aim for autonomous networks, but current networks lack full autonomy due to overwhelming data and noise, requiring AI and automation for improved operations.
MAIN POINTS FROM TRANSCRIPT
- Current networks have partial automation and AI but lack full autonomy.
- Excessive data generation overwhelms human processing capabilities.
- Signal versus noise issues lead to ignored alerts and missed critical signals.
- Data volume and siloed data complicate cross-domain analysis.
TAKEAWAYS
- AI and automation can enhance network operations by filtering noise and identifying critical signals.
- Autonomous networks require integration of AI, automation, and analytics.
- Day zero, one, and two structures are crucial for network planning and operation.
- AI is not a magical solution but a tool to improve network understanding and decision-making.