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TechnologyFinancial servicesAI governance

AI Agent Governance and Cost Control

Give AI platform teams a clearer view of agent ownership, activity and spending, with review workflows for budgets and policy decisions.

01

Connect each agent to an accountable owner

02

Review activity and spending in one place

03

Support budget reviews and audit preparation

Video walkthrough · A representative walkthrough of agent ownership, activity, cost and review workflows. Open video

Industry
Technology
Focus
AI governance
Inputs
Agent inventory, activity logs and cost records
Teams
AI platform, security, risk and finance teams

The business situation

Where this fits

As teams add AI agents, it becomes harder to answer basic questions: who owns each one, what is it doing and where is the cost going? A list of agents is not enough when finance and risk teams also need the activity behind a decision.

For organisations that need common oversight as AI agents spread across teams.

  • Agent ownership is unclear.
  • AI spending is difficult to attribute.
  • Risk reviews rely on disconnected spreadsheets and logs.

The solution

How the solution helps

The governance workspace connects agent records with ownership, activity and cost evidence. Teams can review spending, investigate policy questions and prepare an evidence trail for internal oversight. The first rollout should focus on the environments and activity sources your organisation needs most.

01

Establish ownership

Keep an inventory with a named owner and business purpose for each agent.

02

Understand activity and cost

Inspect supported activity records alongside attributed spending.

03

Review exceptions

Bring budget and policy questions to the people responsible for them.

In practice

Review an agent with rising spend

Follow a cost question from its owner to the activity behind it.

What goes in

Agent inventory, ownership records, supported activity logs and attributed cost.

  1. Find the owner

    Open the agent record and confirm its purpose and responsible team.

    OutputAn accountable owner for the review.

  2. Inspect the activity

    Compare spending with the available usage and activity evidence.

    OutputA focused explanation of what needs attention.

  3. Agree the response

    Review the budget or policy decision with the responsible team.

    OutputA recorded decision and supporting evidence.

How it works

How the workflow comes together

Collection

Collect supported activity and cost metadata from the selected AWS environment.

Governance records

Keep inventory, ownership, tenant access and review records together.

Review workspace

Make activity and spending available to the teams responsible for oversight.

  • AWS activity and cost collection
  • FastAPI
  • Aurora PostgreSQL
  • Governance console

Customer value

What this means for your team

In the workflow

Ownership you can act on

Platform, finance and risk teams can work from a common record of the agent, its owner and the evidence relevant to a review.

Why it matters

More focused oversight

Make cost discussions more specific, reduce manual evidence gathering and give policy questions a clear route to resolution.

Review and control

Keep people in control

  • Define which metadata is collected and how long it is retained.
  • Give each team access to the records it is authorised to review.
  • Set explicit owners and approval rules for budget and policy changes.

Get started

Start with your use case

Start with one team or agent portfolio and the cost or policy questions its owners need to answer.

Useful starting information

  • An initial set of AI agents
  • Access to the relevant activity and cost sources
  • Named owners for finance, platform and risk decisions

Success measures to track

  • Inventory and ownership coverage
  • Time needed to investigate a cost question
  • Completeness of the review record

Fit with your existing systems

Choose the initial AWS accounts and supported log sources, then agree collection, access and retention requirements.

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Your next conversation

Can your teams explain who owns each AI agent and what it costs?

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