AI Security Hub
04AI Security Pillar

Model Behaviour Guardrails

Set the policies and boundaries governing what an AI system may say, recommend, or refuse.

Business focus

Define acceptable behaviour

Why it matters

Security starts with a defined business boundary

Model behaviour guardrails translate business rules into system instructions, refusal conditions, output boundaries, and evaluation criteria.

Business risk

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.

What this pillar covers
  • System policy rules
  • Refusal and safe-fallback logic
  • Output boundaries
  • Reasoning and evidence constraints
Launch reading list

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.

Publishing soon

AI Alignment for Business: Turning Intent Into Verifiable Controls

Turn business objectives and limits into controls that can be tested and reviewed.

Part of the launch series
Publishing soon

System Prompt Security: Why Instructions Are Not Access Controls

Use prompts for behaviour while enforcing permissions outside the model.

Part of the launch series
Publishing soon

Constitutional AI Explained: Principles, Training, and Business Limits

Understand principle-based model training and the controls deployers still own.

Part of the launch series

Questions 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?
Practical control checklist

Put the pillar into practice

  1. 1Document approved and prohibited uses in business language.
  2. 2Define safe fallback behaviour for uncertainty and missing evidence.
  3. 3Keep secrets and permissions out of system prompts.
  4. 4Version policy, prompt, model, and evaluation changes.
  5. 5Test intended behaviour with normal, unsafe, and ambiguous requests.
Review a real workflow

Turn this pillar into operating controls

Map the data, access, approvals, monitoring, and evidence around one important AI use case before expanding it.

Explore the diagnostic