Governance is the arrangement that makes an AI system accountable to somebody after it is running. The syllabus splits it into the standards you are measured against, the data practices underneath, and the routine that keeps both alive.
The standards
ISO publishes the management system standards. ISO/IEC 42001 is the one for artificial intelligence, describing a management system for developing and using AI responsibly, and it sits alongside ISO/IEC 27001 for information security. Certification against it is how an organisation demonstrates a governance system exists rather than asserting it.
SOC reports, System and Organization Controls, are audits of a service organisation's controls. SOC 2 is the familiar one for security, availability, processing integrity, confidentiality and privacy, and it is what a customer's procurement team asks for.
Algorithm accountability laws are the growing category of regulation requiring disclosure, impact assessment or a right to explanation where automated decisions affect people. The specifics vary by jurisdiction and the direction is consistent, which is that a system deciding something about a person is expected to be documented, testable and appealable.
The exam does not test the text of any regulation. It tests whether you know which kind of instrument a given name is.
Data governance
Data lifecycle covers a record from collection to deletion, and the useful question is who authorised each stage. Data collected for one purpose and used to train a model is a different purpose, and consent frequently does not travel.
Retention is how long you keep it. Longer retention is a larger breach and a larger obligation, and training data has a habit of outliving the reason it was gathered.
Residency is where it physically lives. For AI this reaches further than it looks, because inference has to happen in the permitted region too, and not every model is available in every region.
Logging, monitoring and observation are what make an incident reconstructable. For a generative system that means recording prompts, retrieved context and responses, which immediately becomes its own privacy problem, since the log now contains whatever the user typed.
The governance routine
Policies state what the organisation permits, and the useful ones are specific. Which categories of decision may be automated, which require a person, and what data may reach a third party model.
Review cadence is how often a deployed system is looked at again. Bias drifts, data shifts, and providers update models underneath you, so a system signed off once is not governed.
Review strategies cover what a review consists of. Performance by subgroup, sampled human evaluation, incidents since the last review, and whether the documented limitations still match reality.
Transparency standards decide what gets published. Model cards, disclosure that a user is talking to a system, and stated limitations.
Team training appears in the syllabus and is easy to overlook. People deploying and operating these systems need to understand the failure modes, and an untrained team is the most reliable governance gap there is.
The Generative AI Security Scoping Matrix
Named explicitly in the exam guide. It is an AWS framework that places a generative AI use case in one of five scopes, running from consumer applications you merely use, through building on a hosted model, to training your own from scratch. Security obligations differ sharply along that line, and the matrix exists so a team can work out which ones are theirs.
Services the exam names
AWS Config records resource configuration and evaluates it against rules. AWS Audit Manager collects evidence continuously against a framework. AWS Artifact provides AWS compliance reports, which is where a SOC report comes from. AWS CloudTrail logs API activity, so who invoked a model and when is answerable. Amazon Inspector finds vulnerabilities in workloads. AWS Trusted Advisor checks an account against best practice.
The pattern worth carrying into the exam is that Config and Audit Manager are about your configuration, Artifact is about the provider's, and CloudTrail is the record of what happened.