NAN118: The Importance of the Data Behind AI in Networks (Sponsored)

This episode of Network Automation Notes features a live conversation at the Selector AI Summit with Surya, Chief Data Scientist, and Joby, Senior Distinguished Engineer, both from Selector AI. The discussion centers on the critical role of data in AI-driven network observability, emphasizing that while AI and machine learning are powerful, the true 'secret sauce' lies in high-quality, enriched data. Surya and Joby explain how Selector AI uses a foundational machine learning engine combined with a customer-specific modeling language (S2ML) to deliver actionable insights tailored to individual network environments. They highlight the importance of data enrichment, anomaly detection, and the human-in-the-loop approach, where AI acts as a co-pilot to augment, not replace, network engineers. The conversation also explores the future of agentic AI, the need for cross-domain integration (security, application performance, user experience), and how organizations can overcome 'data anxiety' by starting with clear outcomes. Key themes include transparency, continuous feedback loops, and the evolving role of network engineers as architects of intelligent systems. The episode concludes with actionable takeaways for listeners: define clear outcomes before deploying AI, prioritize data quality and enrichment, embrace AI as a co-pilot, and maintain active customer feedback loops. The overall tone is optimistic and forward-looking, celebrating the transformative potential of AI in networking while grounding it in practical, human-centered principles. The hosts and guests express strong enthusiasm for the future of network automation and the power of data-driven decision-making.