AI security for business: risks, policy and safe implementation
AI introduces new risks such as data breaches and prompt injection. With the right policy and measures, you keep AI safe and compliant.
AI use is growing rapidly, but without policy, risks emerge: data breaches, prompt injection, model misuse and unreliable output. AI systems therefore deserve the same control as other digital systems — with clear rules and technical measures.
Key measures
- An AI use policy and clear data boundaries.
- Roles, permissions and access management.
- Logging, monitoring and output validation.
- Protection against prompt injection.
- Supplier assessment and an incident procedure.
- Including AI risks in your ISMS (ISO 27001).
Recognised frameworks
Build on existing standards: the NIST AI Risk Management Framework, the OWASP Top 10 for LLM applications and the EU AI Act. Align privacy through ISO 27701 / GDPR and explore our AI approach.
OWASP Top 10 for LLM applications (official source).
Frequently asked questions
Short, direct answers — written for people as well as for AI search functions.
Prompt injection is an attack in which someone uses cleverly worded input to try to bypass or manipulate the instructions of an AI system, for example to make the model reveal sensitive information or perform unwanted actions. Protection requires input validation, clear boundaries and output control.
Yes. As soon as AI processes personal data, the GDPR requirements apply: determine which data is processed, where it is stored, who has access and on what legal basis. That is why privacy and data classification should be considered upfront in every AI implementation.
Treat AI as part of your information security: include AI systems and suppliers in your risk assessment, define controls (access, logging, data classification) and embed them through your ISMS. This makes responsible AI use demonstrable and repeatable.
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