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Ecosystem guide

Where AI governance fits in the AI control stack

AI governance, cybersecurity, identity, engineering, and runtime enforcement are related but different responsibilities. This guide shows how they fit together—and where Aivance contributes.

The distinction that matters

A secure action is not automatically a governed action.

An agent may have a valid identity, be uncompromised, and hold permission to call a payment API. Governance still has to determine whether it should initiate a particular transfer, under the current authority, context, risk classification, and approval state—and whether the organisation can explain that decision afterwards.

01

Frameworks and regulation

What should the organisation govern?

IMDA, MAS, ISO, privacy obligations, contractual commitments, and internal risk appetite define the expectations. They describe the outcomes and control areas that matter, but they do not by themselves enforce an action at runtime.

02

Governance and assurance

Should this action be permitted in this context?

This is where authority, risk classification, policy, human accountability, intervention conditions, and decision evidence are brought together. Aivance helps define this layer precisely enough for other teams and technologies to implement.

03

Security and identity

Is this agent authenticated, secure, and technically permitted?

Identity, IAM, cybersecurity, cloud, and policy platforms protect systems and provide technical capabilities. They are essential, but a valid identity and permission do not automatically prove that a consequential action is legitimate under governance policy.

04

Engineering and implementation

How is the system built, integrated, and operated?

Internal engineering teams and implementation partners connect agents to data, tools, APIs, and business systems. They turn the control design into a working production capability alongside the organisation’s existing technology stack.

05

Runtime enforcement and evidence

What happens when the agent acts?

The runtime layer evaluates the action against identity, delegated authority, context, data, tool, parameters, policy, and prior actions. It allows, limits, escalates, or denies the action and preserves evidence of why the decision was made.

Aivance’s role

The layer between governance intent and runtime enforcement.

Aivance does not replace your cybersecurity provider, IAM platform, legal adviser, or engineering team. We connect those capabilities by specifying what the system is authorised to do, under which conditions it must stop or escalate, and what evidence must exist when it acts.

Discover

Map systems, agents, tools, data, and owners.

Classify

Assess risk, authority, and obligations.

Authorize

Define allowed actions and approval conditions.

Enforce

Specify the technical controls that must hold.

Evidence

Preserve decision lineage and intervention records.

Aivance does

  • Translate governance and regulatory requirements into control requirements.
  • Define delegated authority, intervention conditions, and evidence needs.
  • Recommend suitable implementation or technology partners where needed.
  • Assess whether controls are technically enforceable and defensible.

Aivance does not

  • Sell a proprietary security or identity platform.
  • Replace your IAM, cybersecurity, legal, or engineering teams.
  • Provide legal opinions or guarantee regulatory approval.
  • Assume implementation, licensing, or operating costs are included.

Find out where your AI governance policy stops and runtime enforcement begins.

Start with the complimentary 30-Minute Enforcement Gap Review. We identify which controls are documented, which are technically enforced, and what evidence is missing. Within 48 hours, you receive a written diagnosis mapped to your applicable frameworks.

Book Your Enforcement Gap Review