The AI Cost 'Black Box' — And How CloudZero Provides Clarity

The AI Cost ‘Black Box’ — And How CloudZero Provides Clarity Into Spend

The booming age of AI means high rates of adoption, accompanied by surprisingly high costs. What makes it challenging is lack of clarity into where your AI investment is going — but CloudZero provides a clear pane of glass not only into the costs themselves, but what you're getting out of them.

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Why AI Spend Feels Like A Black Box From Black Box To Breakthrough With CloudZero

AI adoption continues to explode, and so do their costs.

By mid-2025, enterprise LLM spend had already hit $8.4 billion, more than double the year before. And in a major shift, Anthropic recently overtook OpenAI as the enterprise leader. Their Claude models are now core tools for companies adding generative AI technology into their products and workflows.

CloudZero recently announced we are the first cloud cost platform to integrate with Anthropic. With this integration, you can pull Claude usage and cost data into the same CloudZero platform you already use for AWS, Azure, GCP, SaaS, and other AI workloads.

Now, for the first time, engineering and finance teams can finally see Claude costs side-by-side with the rest of their cloud spend, clearing away the fog that makes AI costs feel like a mystery.

Why AI Spend Feels Like A Black Box

That mystery is a problem. AI costs are a ‘black box’ for many organizations. Pricing models are complicated, and a single misstep — a runaway inference loop or a training job that runs too long — can rack up big, unexpected charges. Add in ‘shadow AI’ projects created by individuals or teams, and the cost risk grows.

There’s a good chance your company is among the 71% of organizations already using generative AI; roughly one-third of surveyed IT/engineering teams report annual LLM spend exceeding $250,000.

Yet very few can answer simple questions: Which team generated that spend? Which product feature drove those costs? Was that investment tied to customer value?

CFOs, for good reason, are demanding answers — 38% say they’re unsure about AI’s cost versus its risk, even as they increase budgets for experimentation and growth.

And 58% of organizations say costs related to on-demand tech (in other words, SaaS and GenAI) are “a big black hole”, according to a Sept. 2025 report released by Capgemini.

From Black Box To Breakthrough With CloudZero

This is where CloudZero shines a light. An example: one CloudZero customer using multiple LLMs has already saved $1 million by optimizing inference workloads and caching tokens. (Around 80% of CloudZero customers already manage AI spend in our platform.)

We bring AI costs into focus by giving you:

1. Unified visibility with CloudZero AnyCost

AI spend doesn’t exist in a vacuum. Most organizations are juggling costs from multiple clouds, SaaS services, and AI providers at once. CloudZero’s AnyCost technology ingests all of that data (whether it’s Claude, ChatGPT, AWS, Azure, or PaaS) and translates it into a common cost model.

Instead of reconciling dozens of billing feeds and formats, engineering and FinOps teams see a unified, real-time view of all spend in one place. It creates a foundation for smarter decisions.

2. Accurate attribution with CostFormation

Seeing total spend is one thing; knowing who or what is driving it is another. CloudZero’s patented CostFormation engine allocates 100% of cloud and AI costs (even untagged or shared resources) to the right products, features, or customers. This level of attribution unlocks true unit economics.

When teams can measure cost per customer or per feature, they gain the clarity to adjust pricing, refine roadmaps, and design architectures that protect margins.

3. Actionable insights in real time

Visibility and attribution are only valuable if they drive action. CloudZero surfaces real-time anomalies, catching runaway workloads or unexpected token usage before they result in sky-high invoices. The platform also helps teams implement best practices like token caching, so inference workloads become more efficient over time.

Instead of finding out about a mistake weeks later, companies can remediate in minutes and prevent waste before it happens. And avoid the surprise bill.

4. Alignment around a single truth

For too long, engineering and finance have looked at AI costs through different lenses. Engineers see technical usage, finance sees invoices, and neither side trusts the other’s data.

CloudZero fixes this by giving both teams the same real-time numbers, in the same platform. Engineers can directly connect spend to design decisions, while finance gets auditable, defensible reporting they can take to the CFO or board.

The result is no finger-pointing, no ambiguity, and a shared understanding of profitability goals. No more AI ‘black box’. With CloudZero, finance and engineering finally speak the same language, a revolution for scaling AI responsibly.

Learn more about CloudZero’s Anthropic integration or contact us to discuss the specific other AI tools you’re using. And our new, must-read report, The AI Cost Optimization Playbook, helps you take control of AI costs and scale responsibly.

Author: David Aponovich

David is CloudZero’s senior product marketing manager. He brings a diverse background in technology as a product marketer, industry analyst, and content management advisor, among others. He’s an amateur outdoor photographer and has more photos on his iPhone than you’d believe.