AI cost allocation
Assigning AI spend to the teams, products, and customers that generate it, by model, API key, project, and person.
AI cost allocation is the practice of assigning spend on AI models and services to the teams, products, features, or customers that generate it. AI providers send one invoice per organization, so allocation starts from usage data: OpenAI breaks usage down by project and API key, Anthropic by workspace and API key, and cloud bills list Bedrock or Vertex AI usage like any other service. Teams map those identifiers to owners, often with a virtual tag rule such as one project or key per team, and split shared spend, such as a common gateway or an internal AI platform, by each team's tokens or requests. Seat-based AI tools such as coding assistants allocate by user and department. With allocation in place, showback and chargeback cover AI the way they cover cloud, and unit costs such as cost per customer include the model bill. LevelFour allocates OpenAI projects, Anthropic workspaces, and cloud accounts to the same teams with virtual tags.
Frequently asked questions
How do you allocate a shared AI API key?
Give each team or service its own project or API key where the provider allows it, which makes the bill allocate itself. For a key that several teams share, route traffic through a gateway that records which team made each call, then split the cost by each team's share of tokens or requests.
Can you charge AI costs back to customers?
Yes, when requests carry a customer identifier. Dividing model spend by each customer's usage gives cost per customer, which pricing and margin decisions depend on once AI features ship inside the product.