The total cost of ownership of enterprise AI.
Every cost an AI workload carries over its life, including the ones that grow with use, and why cheaper tokens can still mean a bigger bill.
- Topic
- AI ROI
- Product
- Novie Control
- Format
- Guide
- Reading time
- 2 min
- Published
- 5 November 2026
The total cost of ownership of an enterprise AI workload is everything it costs over its life: licences, model usage, cloud and data, the build, the people who run it, governance and, in the end, its retirement. Usage costs are the part that moves, and Gartner expects inference cost per agentic workflow to rise more than fivefold through 2028 even as the price per token falls.
The full list of costs.
| Cost | What it includes | Where to find it |
|---|---|---|
| Licences and seats. | Assistants, copilots and AI features in existing software. | Software contracts and card spend. |
| Model usage. | Input and output tokens, reasoning tokens, embeddings. | Provider bills, by project or key. |
| Cloud and data. | Hosting, vector stores, storage, data movement. | Cloud bills, tagged by workload. |
| Build and integration. | Engineering, data preparation, connectors, testing. | Project time and contractor invoices. |
| Operation. | The people who monitor, fix and improve it. | Time records or an agreed share of roles. |
| Governance. | Security review, compliance, audit, approvals. | Risk and legal time. |
| Retirement. | Revoking access, moving work, archiving records. | A planned line in the business case. |
TakeawaySeven kinds of cost make up an AI workload's total, and most organisations only see the first two.
Why cheaper tokens can mean a bigger bill.
Gartner said in August 2026 that product leaders cannot rely on cheaper token economics to rationalise AI costs, because agentic workflows make many more calls, carry longer context and use reasoning models. Its forecast is that inference cost per agentic workflow rises more than fivefold through 2028. In KPMG's survey for the second quarter of 2026, 29 percent of leaders reported difficulty understanding and controlling operating costs as systems scale.
TakeawayThe price per token falls while the tokens per task rise, so agent costs have to be read per workflow.
How to keep the total in view.
- Give every AI workload an identifier, and tag its keys, projects and cloud resources with it.
- Bring provider bills, cloud costs and licences into one view by workload, each month.
- Add the people and governance costs as an agreed monthly figure.
- Set a budget per workload, with a cap on usage-priced spend.
- Compare the total with the business case at each review.
TakeawayOne view of every cost, by workload, each month, is what turns the total cost of ownership into a number finance can use.
How Novie Control does it
You can see what AI costs to build.Can you see what it costs to run?
Sources
- Gartner, Predicts AI Inference Costs Per Agentic Workflow Will Increase More Than Fivefold Through 2028 (17 August 2026)
- KPMG International, Global AI Pulse Q2 2026 (June 2026)
- Gartner, Survey Finds Only 13% of CIOs Say Their Enterprise Has Realized Significant or Transformational Value from AI (19 October 2026)