What you’ll gain
- Security and assurance: keep data boundaries clear and in control
- Cost control: right-size your approach to optimize TCO
- Auditability: transparent logs and permissions you can explain anytime
- Choice: select OSS/commercial models and locations that fit your context
Key points
- Data boundaries: classify what you handle and where it flows
- Operating model: choose where models run and how they’re accessed
- Access and keys: least-privilege, rotation, and simple guardrails
- Logs and retention: keep just enough records, mask what’s sensitive
- Cost thinking: scale sensibly; improve before you over-provision
Expected changes (In-house AI)
- Peace of mind: run AI with privacy, regulatory, and policy needs in mind
- Predictable spend: reduce waste and avoid surprise growth in usage
- Explainability: be able to show who used what, when, and how
- Flexibility: adapt stack and models as needs evolve