Agentic AI Governance
for Established Businesses
Agentic AI can dramatically increase the efficiency of your organisation, if deployed well. We help smaller businesses to get agentic AI governance in place, before they have to scramble to keep agents in check.
Agent asks to act
Rules are checked
Action is logged
You can see who allowed each action and why.
What is agentic AI?
There are two main types of business AI right now. Assistive AI produces a result that a human uses, writing a draft, analysing an image, whatever. Agentic AI is able to act on your behalf. For example, an agent might be able to:
Read your inbox, respond to simple questions and escalate tricky ones
Update your CRM
Create invoices from contracts
Email clients
Existing generative AI policies are unlikely to provide adequate governance for these sorts of AI. That’s where we can help.
What sorts of problems can agentic AI have?
In December 2025 OWASP published its Top 10 for Agentic Applications, drawing on vulnerabilities seen in real-world agentic applications. Broadly speaking:
Agents can be manipulated into performing actions that are not desirable, known as prompt injection. This can occur through data that agents encounter, like emails, documents, websites, etc.
Agents can be given more agency, meaning ability to take actions, than they need to perform their task
Agents can mis-use tools, meaning calling them with the wrong arguments, or acting on the wrong records
Their activities may not be observable enough to trust them with sensitive or high-volume tasks
Agentic tools may be introduced into an organisation without IT or Dev teams being aware, known as shadow agents
How do I know if I need agentic AI governance?
Put simply: if you have agents, or are planning to introduce them. Risk depends on what they’re allowed to do, not on the size of your organisation. A thirty-strong business could be putting itself at risk with a refund-handling agent, whereas a large organisation might have lots of agents that don’t write to production systems.
The longer you leave it, the more awkward and expensive this is likely to be. It’s much simpler to implement these sorts of controls when you’re building your first agent than it is to go back later when you have lots of agentic automations running around the place.
What does agentic AI governance consist of?
A risk assessment of what you have, which systems do agents interact with? Are there controls around the actions they can take?
A short, practical policy: what sorts of agents are acceptable? Which data can agents have access to? Who owns them? How do you approve them?
Technical guardrails in place to make sure they’re doing what they should be doing
Testing and monitoring to make sure they stay on track
We follow NCSC’s guidelines for securely building and using AI, and will ensure your systems are aligned with the EU AI Act where relevant, ignoring the parts that aren’t relevant to businesses of your scale.
Our services are practical and pragmatic, we’ve seen agentic systems in action and know what works and what doesn’t. We can help you build a governance approach that enables your teams to build agentic systems faster, not slower.
What does the process look like?
Broadly speaking there are four parts to our approach:
Build a picture of your current agents, their capabilities, and risks. The output is a risk map showing what systems your agents can read, write, and make decisions about, and the blast-radius of errors.
Build a policy, we’ll make it as short and simple as we can. The goal is that someone can pick it up, understand it, and start making sensible decisions about agentic AI in your organisation.
We can help you build in technical guardrails, for example:
Validating actions taken by agents in application code, not just with prompts
Spend and volume caps
Requiring approval for some actions
Set up monitoring, evaluation, and governance. Agents should be tested before they’re deployed, we’ll help you define evaluation sets. Their actions should be logged and monitored, we’ll make sure they are. Once in place we’ll run a red-team exercise to make sure they’re not going to be able to be steered off-course.
How long does agentic AI governance take?
The answer is always “it depends”. Projects will be bigger if you have lots of agents, especially if they have write-access to production systems. We’ll be able to provide a better estimate once we’ve carried out our first step, an inventory of your agents and their capabilities.
What happens next?
Tell us a bit about your agentic systems, current and planned, and their capabilities. Then book a call to discuss agentic AI governance.