AI agents introduce an entirely new class of risks. At Agentic Risks, we use our proprietary agentic AI controls framework and real-world experience within a regulated environment to help firms adopt agentic AI workflows safely and with confidence. De-risk your transformation by developing a broad agentic capability, rather than just building agents.
Autonomous AI agents bring significant advantages to organisations.
These include higher productivity, scalable automation, and better use of human judgement.
Agents deliver these benefits because they can:
This makes AI agents more powerful than basic prompt-driven AI tools.
However, while AI agents can perform tasks on our behalf, they need external controls because they are immune to traditional ethical sanctions.
Because of this, to leverage the benefits of delegating autonomy to this new technology, you must manage the new class of risks it introduces.
If left unmanaged, agentic risks can materialise across individual and multi-agent behaviours, system security, governance, policy integration, as well as organisational and human factors.
Understandably, many organisations are unfamiliar with the risks, and traditional controls are insufficient.
Despite this, regulators and standards bodies are clear: firms must integrate agentic risks into their existing risk management frameworks.
To overcome this, our Enterprise-Wide Agentic AI Risk Control Framework contains the full set of known agentic risks and the latest best-practice controls.
With it, you can:
An agentic AI controls framework is a structured set of policies, safeguards, and checks that keep AI agents aligned with your goals and operating safely. It sets the rules for how AI agents behave, what they can and cannot do, and when humans need to stay involved.
To implement agentic AI controls, set your policy on AI autonomy, map the risks and controls for a pilot agentic workflow, and prove control effectiveness through testing. Once your pilot is live, confirm your new agentic capability is audit-ready, and then increase your stakeholder engagement through additional risk assessments as you launch new agentic workflows.
AI agents do not stay in one team or system. If controls apply only to one area, risks and failures will spread, for example, costs need to be managed, business continuity teams need to be ready for new incident types, management information need to reflect your new non-human workforce, and leaders need to manage the human factors. Making your agentic AI risk controls enterprise-wide ensures consistent standards, shared accountability, safer scaling, and fewer gaps that could lead to errors, breaches, or misuse.
Agentic AI risk controls protect against misaligned agent behaviour, loss of oversight, security weaknesses, compliance failures, and poor handovers between humans and agents. With the right controls, organisations reduce the risk of errors, reputational harm, and unintended autonomous actions.
Responsibility normally sits with a senior leader, such as a Head of AI, Chief Risk Officer, or technology governance lead. Business teams, risk, compliance, and IT should all play a part in mapping risks to controls.
Yes. Smaller organisations often adopt AI agents faster and with fewer internal checks, which increases risk that a smaller firm may be less able to handle. The Agentic Risks framework allows them to construct proportionate risk treatment plans by selecting only the controls that apply to them without prescribing they do more than they need to.
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