HAIAMM vs Google SAIF
Google Secure AI Framework
A set of secure-AI engineering principles and a risk map from Google, aimed at guiding how teams reason about securing AI systems and supply chains.
✓ Pros
- Practical, engineering-led principles from a large-scale AI operator.
- Good coverage of the model and application layers and the AI supply chain.
- Accessible mental model for teams starting to threat-model AI.
- Free and public.
⚠ Cons / Gaps
- Principles and risk map, not a maturity model, no levels and no program score.
- Not an assessable standard; provides direction rather than measurable criteria.
- Centered on model/app layers; lighter on vendors, endpoints, and organizational process.
- No certification or formal assurance path.
Why HAIAMM is a strong choice
- HAIAMM turns SAIF's principles into assessable, tiered practices with measurable outcomes.
- HAIAMM extends the same rigor to Vendors, Infrastructure, Processes, and Endpoints, areas SAIF lightly touches.
- HAIAMM gives a program-level maturity score SAIF does not attempt.
How they work together
Adopt SAIF's principles as design guidance; use HAIAMM to measure how mature your program is at actually implementing them across the full AI estate.
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