5 Big Myths of AI and Agentic AI Debunked

It’s hard to believe that artificial intelligence (AI) and machine learning (ML) have been around since the 1950s. While ML became mainstream in the early 2010s, more sophisticated types of AI have evolved from academic concepts to everyday business tools over time. The rise of large language models (LLMs) in late 2022 made AI more accessible than ever and drove the adoption of generative AI (GenAI) tools. And now, the application and prominence of agentic AI have become the next frontier.

Today’s AI can do far more than answer prompts. From summarising noisy incidents and correlating telemetry to recommending next steps, autonomous agents leveraging agentic AI are becoming a force multiplier for both security and observability teams.

Agentic AI often comes with built-in expertise and can interpret and process information from its environment in a meaningful way, enabling it to make informed decisions and take actions. While this gives teams new advanced capabilities based on an inherent understanding of various domains to get ahead of security and performance issues, it also has the potential to upend traditional monitoring and SOC activities.