Host Greg Bryan welcomes Jason Gintert back to the show. As the incoming President of the U.S. Networking User Association, Jason dives into the current state of AIOps in network management.
This includes:
- Low Adoption and Key Challenges: Despite being a popular topic, AIOps adoption remains low due to concerns about trusting AI output (hallucinations) and the indeterminate nature of large language models.
- Data Integration and Security: The importance of integrating private data using methods like the model context protocol to make AI answers more deterministic. For security, Jason strongly recommends starting with a read-only, zero-trust mindset when exposing data to AI tools.
- Practical Use Cases: AI is most valuable for root cause analysis of common network problems (e.g., Wi-Fi authentication issues, circuit errors) and providing automated network summaries or predictive analysis.
- The Human Element: AI is seen as a powerful tool to increase the productivity of network engineers by handling low-level tasks, but it will not replace humans. Engineers remain crucial for exercising judgment and taking responsibility for service-impacting changes.
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