UNDERSTANDING THE TRUE COST OF ENTERPRISE AI

It's not just what you spend on AI. There are hidden costs with every new initiative, and a way to reduce them.

Visible costs of models, GPUs, tokens, and inference above hidden costs of finding data, copying datasets, security and compliance, and building pipelines

Visible costs versus hidden costs of enterprise AI

The visible cost of AI

Enterprise AI has a price tag everyone can see: the models, the infrastructure, the tokens, the compute. It all costs money, and you know what you're spending.

But that's not the whole cost

Before any of that spend pays off, your data has to be ready for AI use. And much of that readiness work repeats with every new initiative.

Technical readiness: discovery, classification, permissions, pipelines, indexing, retrieval, refresh, recovery

Business-approved use: business context, ownership, governance, review, and approval

The hidden work doesn't scale

Right now, you have to manually find, select, copy, and feed the right context to AI yourself. That may work for a quick prompt or an experiment. It doesn't work for your most sensitive, regulated, or distributed enterprise data, spread across every team and use case.

So you pay an AI-readiness tax

Every AI initiative that starts from scratch repeats this work: rebuilding the same data pipelines, controls, and access paths again and again.

Think of this as an AI-readiness tax: the recurring engineering effort, delay, duplication, and risk involved in making enterprise data ready for production AI.

World map of distributed enterprise data locations

Smartphone with data insights and a payment card

Why not build on what you already have?

Good news: You don't have to build a new data foundation for every AI project if your data is already protected with Cohesity.

That foundation—discovery, classification, permissions, and protection—is already in place.

Here's how it works

The Cohesity Data Cloud provides the protected data foundation.

Cohesity Gaia Catalog puts it to work by helping teams discover, organize, enrich, and govern relevant data for use across AI and data platforms.

From there, Cohesity Gaia lets users securely search, summarize, and derive insights from that data through agents and copilots. Governance and permissions carry forward instead of being rebuilt, across SaaS, hybrid, and fully air-gapped deployments.

Magnifying glass revealing insights in protected data

See how to put your protected data to work

Explore Cohesity Gaia