Model Behaviour Guardrails
Set the policies and boundaries governing what an AI system may say, recommend, or refuse.
Define acceptable behaviour
Security starts with a defined business boundary
Model behaviour guardrails translate business rules into system instructions, refusal conditions, output boundaries, and evaluation criteria.
A well-written prompt is not an access control or a guarantee. Businesses need explicit rules for acceptable use, uncertain answers, restricted topics, and situations that require human judgment.
- System policy rules
- Refusal and safe-fallback logic
- Output boundaries
- Reasoning and evidence constraints
Turn define acceptable behaviour into repeatable controls
A policy is only the starting point. For each AI use case, name the business owner, define the allowed boundary, configure the relevant technical controls, and decide what evidence proves those controls are working. Repeat the review when the model, data, connected tools, or business purpose changes.
Start with a single high-value workflow instead of trying to govern every experimental use at once. That makes it possible to test the controls with real users, find exceptions, and create a pattern the rest of the business can reuse.
Start with these practical guides
Each pillar begins with one anchor guide and two supporting articles. Published guides become active automatically as they enter the blog.
AI Alignment for Business: Turning Intent Into Verifiable Controls
Turn business objectives and limits into controls that can be tested and reviewed.
Read the guideSystem Prompt Security: Why Instructions Are Not Access Controls
Use prompts for behaviour while enforcing permissions outside the model.
Read the guideConstitutional AI Explained: Principles, Training, and Business Limits
Understand principle-based model training and the controls deployers still own.
Read the guideQuestions for leadership
- Which outcomes are acceptable, restricted, or prohibited?
- When should the AI refuse, defer, or ask for approval?
- Who can change system policies and prompts?
- How are guardrails tested after model or workflow changes?
Put the pillar into practice
- 1Document approved and prohibited uses in business language.
- 2Define safe fallback behaviour for uncertainty and missing evidence.
- 3Keep secrets and permissions out of system prompts.
- 4Version policy, prompt, model, and evaluation changes.
- 5Test intended behaviour with normal, unsafe, and ambiguous requests.
Use recognised guidance to validate the control design
These resources help teams translate AI-specific risks into documented, testable business and technical controls. Apply them to the actual data, permissions, and actions in the workflow rather than treating them as a one-time compliance exercise.
- NIST AI Risk Management Framework
A lifecycle-oriented framework for governing AI risk.
- OWASP Securing Agentic Applications
Practical secure-design guidance for AI systems that use tools.
- CIS AI and LLM Companion Guide
AI-aware interpretations of established security controls.
Turn this pillar into operating controls
Map the data, access, approvals, monitoring, and evidence around one important AI use case before expanding it.