Operations | Monitoring | ITSM | DevOps | Cloud

AI costs are changing. As noted by research from EY, outputs that cost just $0.04 in 2023 now cost $1.20, a 30x increase over just three years. It’s worth noting that task operations and complexity have also changed. In 2023, the process was simple. Users input a question, retrieval engines found relevant data, and AI models returned a response. Today, many tasks are handled by orchestrated AI agents capable of much more complex reasoning and analysis.

When the changelog doesn’t keep pace with the product, two things can happen. One, you keep working around something that was already fixed weeks ago. Or two, a behavior changes, you assume it’s a bug, and you spend an afternoon on triage and a support ticket before learning it was an intentional improvement. CloudZero now ships around 30 improvements a week, a pace driven by the Next Gen Platform and the AI-first approach we’re building for our customers.

Anthropic, the company behind Claude, ran the most honest experiment in agentic AI: they gave a version of their own model $1,000, a small fridge in the office lunchroom, and one job. Run a shop. Make a profit. They named it Claudius. Claudius did not make a profit.

Instead of building a separate role for every team, region, or department, admins can create a single role that automatically personalizes access for each user based on their SSO attributes. Someone moves teams or a new group gets created, and the new access takes effect at their next login with no CloudZero configuration. As AI spend grows, more companies are looking to give teams visibility into their own AI costs without exposing every individual’s usage across the org.

Every finance person I know lives in the same loop approaching the end of the month, quarter, or fiscal year. Leadership wants to know where the financials will land (most times before the close has occurred). CS wants customer margins. Someone on the People team needs each department’s AI spend for an OKR review, and they need it quickly to make business decisions. Each answer sits in a different tool or a different spreadsheet, and I bounce across all of them several times a day.

You are mid-investigation, chasing a spike or pulling a number for finance, and you hit a term or a workflow you need to look up. You should not have to lose your place to find an answer. Guide lives in a fixed spot in the left sidebar, always one click away. It opens a panel on the right side that sits beside your page instead of covering it. Your chart, filters, and time range stay exactly where they were. Nothing gets rebuilt and you keep the thread of what you were investigating.

Hyperscale providers are nothing if not consistent in their temptation of enterprise IT buyers. They bombard leaders with a simple message: migrate to the public cloud, shut down data centres, and enjoy both financial savings and operational agility. However, as UK enterprises have scaled their digital footprints, a more nuanced reality has bitten. Public cloud costs have swollen.

Budget season is starting and most finance teams are finding the AI line is the most evasive line on the page. You lived through the year. AI spend came in higher than planned and moved in ways nobody could foresee or forecast. And when the board asked what it produced, the honest answer probably was “we’re working on it.”

People run Codex on their own laptops. When Codex is signed in with a ChatGPT subscription, OpenAI’s own admin console shows who used it and how much: messages and credits. What it doesn’t show is what any of that usage was for, or how it compares to what your team spent on other AI tools. The CloudZero desktop agent for macOS installs on a Mac, sees the traffic from AI coding tools, and prices what those tools use.

AI is expensive because the model bill is only part of the cost. Three components set the floor: model subscriptions, per-token API pricing, and infrastructure. Three more make it move: adapting models to your business, catching and fixing errors, and rising energy and datacenter costs. Efficiency doesn't fix it, because cheaper AI gets used more, not less. Businesses are willing to spend on AI. Research from Deloitte found that in 2025, 85% of organizations increased their AI investments.