Start small. Prove it. Then scale.

For leadership teams deciding where AI agents should go first.

• The one workflow where an agent pays
• A baseline and an honest value case
• A named owner and a go or no-go

Outcome: a decision, not a deck.

For leadership teams setting where AI, and agents, should create value first.

• Use cases ranked by value, risk and readiness
• Operating model and decision rights for AI
• Platform-agnostic architecture choices
• A sequenced 12-month roadmap with owners

Outcome: a roadmap your board can approve and your teams can execute.

For boards, executives and delivery teams who need to govern and build with AI.

• Board and executive sessions on AI and agent oversight
• Hands-on training for risk, model validation and product teams
• Practical exercises on the Agent Studio

Outcome: teams who can ask, and answer, the right questions.

For an agent that works in pilot and is stuck at approval.

• Workflow baseline and cost model
• Every action the agent can take, tiered by risk
• Named owner, delegated authority and limits
• Configured controls, test results and a timed stop drill
• KPI dashboard and an evidence package for model risk

Outcome: a production-readiness assessment and a deployment recommendation, or a documented decision not to deploy. Your institution makes the production decision.

For institutions that need to know what AI they actually run.

• All AI found, including vendor and shadow AI
• Each system tiered by risk and given an owner
• Data readiness scored
• Exposure ranked against your examination calendar

Outcome: a register you can stand behind and a 90-day plan.

For institutions putting the operating model in place across all AI.

• Governance charter and decision rights
• Risk tiering and validation aligned to model risk guidance
• Agent controls and monitoring
• Board and committee reporting

Outcome: AI governance that runs as part of the business.

For keeping governance current between examinations.

• Periodic re-scoring and control testing
• Vendor AI changes reviewed
• Board reporting and examination preparation

Outcome: no surprises at the next exam.

For institutions that need senior AI leadership now, without a full-time hire.

• Executive presence with the board and committees
• Ownership of the AI portfolio and the next agents
• Examiner engagement

Outcome: a Chief AI Officer when you need one.