Table of Contents
Executive Summary
Our Agentic AI Control Design Package turns your governance policy into controls you can implement, own and evidence: an agent tiering framework with practical thresholds, a Statement of Applicability that identifies which agentic risks apply and why, and a Control Log specifying each control, the evidence it requires, and its owner.
We build on your existing policies and controls to support repeatable, controlled adoption at pace, staff confidence and stakeholder trust.
We draft or refine the control design before workshops where your colleagues agree owners, evidence requirements and implementation actions. You receive an agreed design and implementation plan, with guidance and handover to your implementation team.
If you want to adopt different types of autonomous agents safely and with confidence, contact us to customise your Agentic AI Control Design Package.
Agentic AI Introduces a New Category of Risk
Whereas generative AI produces outputs for our review, agentic AI’s ability to plan, invoke tools, and take actions can create outcomes in our name.
Because of this, your risk exposure relates to the behaviours you authorise (or fail to prohibit), e.g. data reach, action space, reversibility, autonomy.
Platform providers are making the tools to build agents easily available, meaning this leap in risk exposure can feel like just another technology upgrade, raising the prospect that your agent estate expands faster than your capacity to control it.
Your Capacity to Build Can Outrun Your Capacity to Control
If this happens to you, without, for example, a complete view of your live and retired agents, you may not be able to reconstruct decisions your agent took or even test your ability to stop them, risking post-deployment remediation costs and longer-than-necessary build cycles.
Firms that get ahead of these problems tier their agents, identify applicable risks, define controls and evidence requirements, and name their owners. They implement and test those controls to support wider adoption and more advanced agentic workflows.
An Agentic AI Control Design Package Gives You the Detail You Will Need
Our Agentic AI Control Design Package translates your governance into a customised agentic AI control design your engineers can configure, your procurement colleagues can licence, your owners can operate, your auditors can test, and for which your HR team can train future talent.
Specialist guidance and handover support pace and internal capability as your agentic risk capability develops. Documented control design supports your due diligence and gives you a reusable foundation for future deployments.
Its key deliverables include:
- An agent tiering framework where an agent can be assigned to a tier based on its authorised behaviours, each tier carrying a written threshold.
- A unique ‘Statement of Applicability’ for agentic risks that identifies which of our 32 agentic risk flags apply to your stage of agentic development. Exclusions are justified, each with a review trigger in case risk exposure presents itself as your agentic capabilities become more advanced.
- A bespoke Control Log of specific agentic AI risk controls, the technical or procedural mechanisms that deliver them, the evidence they produce, what makes that evidence satisfactory, and named owners – with no unagreed blanks.
- Define clear escalation channels for control failures and risk concerns.
- Control configuration requirements specifying what to set, in which system, and at what threshold, for the agreed scope.
- An implementation plan setting out actions, owners, dependencies, target maturity levels and any interim controls.
- An optional Control Set Suitability Statement explaining why the controls fit your agreed scope.
A control without a threshold is toothless, evidence without a standard is untested, and an exclusion without a review trigger becomes a blind spot. So, these details ARE the point.
We design the controls for your control owners’ approval, specify evidence requirements, and advise on implementation. Your engineers or delivery partner configure and implement the controls, test their operation and retain the evidence. We can introduce a delivery partner if you need support.
Two Components Tailored to Your Starting Point
1. General Controls Component – analyse your operational environment and design the platform-independent controls it needs, for example, ownership, an agent register, identity and access, monitoring and incident management.
2. Platform-Specific Controls Component – specify controls and configuration requirements for five priority use cases on one selected agent platform, such as Copilot Studio or Foundry. Confirm the scope against your architecture and licences.
Start with either component, depending on the maturity of your existing controls. If you want a structured view of where and how to act, the Agentic AI Readiness Assessment maps 17 prerequisites across strategic, technical and operational, and organisational readiness to guide your starting point and priorities.
Each component typically takes 6–8 weeks, depending on your availability, and ends with an agreed design and implementation plan. Agree the scope, workshops and participants before commissioning each component.
We Will Help You Overcome the Obstacles
Obstacle 1: “I don’t know where to start!” Your Agentic Risks consultants will draft or refine your tiering framework, Statement of Applicability and Control Log before the workshops. Your colleagues then agree applicability, owners, target maturity levels, satisfactory evidence and implementation actions. We consolidate the agreed design and implementation plan and hand them over to your team. We agree the number, length and attendance of workshops with you at scoping.
Obstacle 2: “Generic controls feel too abstract to act on.” We break down your use cases into underlying agentic capabilities, map them to the Control Log, specify configuration requirements and define the tests and records needed to show the controls work. Workshops use practical examples, including edge cases that test the boundaries.
Obstacle 3: “Help! We’re deploying before we’re fully ready.” While you develop your agentic capabilities, controls can have interim substitutes. Still, we will make sure any interim control carries a review trigger and the condition under which you should retire it and switch to a permanent solution.
Obstacle 4: “How do we keep controls aligned as our agents develop?” Build capability component by component, each ending with an agreed design and implementation plan. Review and adapt controls when agent capabilities materially change. Commission a Platform-Specific Controls component for each new platform, with no commitment beyond the component you commission.
Obstacle 5: “We’re afraid of getting locked-in.” Agentic Risks and our agentic AI governance and control frameworks are platform independent. The general control design provides a reusable foundation. Platform changes require a review of controls and configuration requirements.
Obstacle 6: “We’ve already invested in governance and don’t want to start again.” We start from your existing policies, tiering framework and controls, identifying which controls to reuse, which to strengthen, and where agentic-specific controls are needed.
Agentic Risks Can Make This Story Come True For You
With Agentic Risks’ senior consultants and engineers, you will be in safe hands.
- We specialise in agentic risk assessment and control selection, drawing on a library of more than 250 agentic AI controls; naming artefacts that prove controls work and knowing where to locate each one.
- Our Risk-Based Agentic AI Adoption Strategy gives us deep knowledge of agent tiering; our independence means we will always propose a solution that best fits your needs; and our seniority allows us to facilitate decisions that are both executive in tone and technical in substance.
So, if you want to keep pace with agentic AI or would like some help to move faster, contact us to discuss how our Agentic AI Control Design Package will help you adopt autonomous agents safely and with confidence.
Frequently Asked Questions
Agentic AI control design turns the behaviours an agent is authorised to perform into explicit thresholds, controls, evidence requirements, and ownership. In the approach described here, that means an agent tiering framework, a Statement of Applicability for agentic risks, and a Control Log. The Package also supplies control configuration requirements and an implementation plan, with an optional Control Set Suitability Statement.
Generative AI produces outputs for review, whereas agentic AI can plan, invoke tools, and take actions that create outcomes in your name. That makes risk exposure depend on authorised behaviours such as data reach, action space, reversibility, and autonomy, so the controls need to address those behaviours.
The design described here has three core artefacts: an agent tiering framework with written thresholds; a Statement of Applicability identifying which agentic risks apply and why; and a Control Log recording the mechanisms, evidence, evidence standards, and named owners for each control. The Package also provides control configuration requirements and an implementation plan. An optional Control Set Suitability Statement explains why the controls fit the agreed scope.
A Statement of Applicability identifies which of the 32 agentic risk flags apply at your current stage of agentic development. It also justifies exclusions and records a review trigger for each, in case your risk exposure changes.
For each control, define the technical or procedural mechanism, the evidence it should produce and what makes that evidence satisfactory, then assign a named owner. Your implementation team configures and implements the control, tests its operation and retains evidence. Our Package specifies the design and evidence requirements.
Use interim controls only with a review trigger and explicit conditions for when they should be retired and replaced by a permanent solution. Our Agentic AI Control Design Package helps you develop capability component by component, each ending with an agreed design and implementation plan. Your organisation decides when to deploy, based on implementation and testing.
