AI widens the attack surface
Models, prompts, RAG sources, connectors, credentials and suppliers all introduce new assets and dependencies. ISO 27001 provides a framework for handling them systematically, without reducing security to a list of tools.
AI security is designed in from the first piece of data, model and integration; it is not bolted on once the system is already in production.
Bring AI into the scope of the ISMS
Identify data, integrations, accounts, models, users and third parties. Define which processes the system covers and which interfaces fall outside it. Without a documented scope you cannot assess or demonstrate control.
Assess the specific risks
- Data leakage through prompts, documents or connectors.
- Excessive access by agents or service accounts.
- Manipulation of sources, instructions or outputs.
- Supplier dependency and uncontrolled changes.
- Unavailability, anomalous costs and loss of traceability.
Select operational controls
Apply least privilege, information classification, authentication, logging, source validation, supplier management and incident response. Data quality is also a security control when it stops erroneous or unauthorised information from feeding the system.
Measure and improve
Audit access, test results, incidents, changes and control effectiveness. An ISMS stays alive through management review and corrective actions; AI demands the same discipline after every new integration or version.
Conclusion: build security into the AI lifecycle
Aligning AI systems with ISO 27001 turns technical and organisational risks into verifiable controls. Security must accompany every phase, from choosing data and suppliers through to daily operation.
If you need to design AI systems aligned with ISO 27001, protect information and define controls from the outset, at Impulsa3 we support you with a practical, data-driven strategy.
