Operations | Monitoring | ITSM | DevOps | Cloud

Over the last couple of years, nearly every network and infrastructure observability platform has added the word “AI” to its messaging. Some have introduced helpful capabilities. Others have simply added a chatbot on top of the same dashboards that have existed for a decade. In many ways, the term has started to lose meaning. But inside network operations, the conversation hasn’t disappeared. It has simply become more blunt.

Artificial Intelligence has become the sharpest tool in the digital arsenal – detecting anomalies, predicting failures, and uncovering risks before they unfold. Yet even the smartest system can’t roll up its sleeves and fix what’s broken. AI can see the problem. But only people can solve it. That’s the critical gap in today’s automation revolution: turning AI’s insight into human action.

Nowadays, AI agents are becoming more and more popular and often deployed as part of production systems. However, this rapid adoption brings unique observability challenges that require flexible solutions. On the one hand, AI agents are fundamentally just like any other software services that produce the same classic observability signals we’re familiar with: metrics, logs, and traces.

We’ll always remember 2025 as the year AI code assistants went big. Copilot, Cursor, Claude, Windsurf, whatever. Developers went from mistrusting these tools, to being expected to turn over much of their coding labor to them. Even if, according to an extensive Stack Overflow survey, only 3 percent of professional developers say they ‘highly trust’ AI coding tools.

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Josh Mesout (Chief Innovation Officer at Civo) took the main stage at Civo Navigate London 2025 to deliver a critical message: The AI revolution isn't just coming, it's here, and the way companies are built is changing faster than ever before. His session cut through the hype, delivering hard data on what separates the companies that scale AI from the ones that sink money into failed prototypes. The takeaway is blunt: The biggest threat to your AI ambition isn't the model; it’s your infrastructure.