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GLOSSARY

What is Policy-Native AI?

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Quick Answer

Policy-Native AI is artificial intelligence that has business policies, regulatory requirements, and compliance rules embedded at its core architecture. Unlike traditional AI that learns patterns from data alone, Policy-Native AI enforces constraints, validates against regulations, and ensures every decision complies with enterprise policies and legal requirements.

Definition

**Policy-Native AI** integrates business rules, regulatory frameworks, and compliance requirements directly into the AI's decision-making architecture. Rather than applying policies as post-processing filters, the AI reasons within policy boundaries from the start, guaranteeing that all outputs are compliant by design.

Key Points

  • Business policies and regulations are embedded in the AI architecture, not added as filters
  • Every decision is automatically validated against compliance requirements
  • Prevents non-compliant decisions at the reasoning stage, not after the fact
  • Maintains full audit trail of which policies were applied to each decision
  • Updates policies centrally without retraining the entire AI model
  • Reduces compliance risk by ensuring AI never violates enterprise constraints

When NOT to Use This

  • When business policies are not well-defined or constantly changing
  • For exploratory AI applications where constraints would limit valuable insights
  • When policy violations are acceptable and can be filtered later
  • For non-regulated industries with minimal compliance requirements

Frequently Asked Questions

What types of policies can be embedded in Policy-Native AI?

Business rules (e.g., coverage limitations, approval thresholds), regulatory requirements (HIPAA, state insurance laws), operational policies (escalation rules, documentation requirements), and ethical guidelines (fairness constraints, bias mitigation rules).

How do you update policies in Policy-Native AI?

Policies are stored separately from the AI model and can be updated without retraining. When regulations change or business rules evolve, policy updates are deployed centrally and immediately affect all AI decisions going forward.

Does Policy-Native AI slow down decision-making?

No. By integrating policies into the reasoning process, Policy-Native AI is often faster than systems that filter outputs after the fact. The AI never wastes computation on non-compliant alternatives.