Operations | Monitoring | ITSM | DevOps | Cloud

There's a moment every engineering leader hits when implementing AI where they realize that no one really knows what they're doing. Not your competitors. Not the consultants. Not even the executives pressuring you to show results yesterday. Everyone is figuring this out in real time, and beneath the confident vendor pitches and LinkedIn thought leadership, the truth is messier than anyone wants to admit.

FinOps teams have been expected to understand millions of dollars in cloud and AI spend using tools that a handful of (usually technical) specialists can operate. Dashboards, filters, exports, and SQL have been the norm. That era is over. CloudZero is now bringing AI directly into the FinOps workflow so anyone in the business can ask natural-language questions about cloud and AI spend, and get accurate answers back from the platform.

This blog is based on an Upsun livestream discussion featuring Guillaume Moigneu, Field Engineer, and Thomas di Luccio, Product Manager at Upsun. The conversation was moderated by Greg Qualls. We utilized AI tools for transcription and to enhance the structure and clarity of the content. When Black Friday approaches, the stakes are high for eCommerce businesses.

IT leaders want AI that moves the needle without blowing up risk, cost, or changing control. Your teams need a path to productize AI features on top of existing apps, connect safely to external models, and satisfy audit requirements without slowing delivery. Those are the core buying criteria we hear from IT middle management: buy over build, predictable outcomes, and a strong compliance posture.

Imagine sending a letter to your neighbour across the street, only for it to be routed through London or even Amsterdam before landing in their letterbox. This is effectively what happens to much of Scotland’s internet traffic. Despite physical proximity between users, businesses and services, digital data is frequently sent on needlessly long journeys, often leaving the country before reaching its destination.

Imagine for a moment that agentic coding tools really do deliver on their promise. Code is written faster, tests are generated automatically, and refactors that once took days now take minutes. On paper, software delivery should accelerate dramatically. Now imagine you work in a regulated enterprise. The code is ready, but production is still days or weeks away.

Recently, we introduced autonomous validation as a new approach to CI/CD that brings adaptive, context-aware intelligence into the delivery pipeline. As AI increases both the volume and reach of code changes, teams are seeing more failures, longer queues, and rising maintenance costs. Traditional pipelines simply weren’t built for this level of velocity or variability.