AI RUNTIME READINESS CHECKLIST (2026)

Use this checklist before you call your product “enterprise-ready.” If you can’t answer an item cleanly, assume a real buyer’s security/platform team will block rollout.

1) IDENTITY & ACCESS
- SSO: Do you support Okta and/or Microsoft Entra ID via SAML/OIDC?
- Provisioning: Do you support SCIM so access can be managed by groups, not invites?
- Role model: Are roles explicit (admin, developer, auditor, user) with least-privilege defaults?
- Service accounts: Can customers create scoped service identities for automation?

2) POLICY ENFORCEMENT (NOT “GUIDELINES”)
- Enforcement point: Where is policy enforced—SDK, gateway, proxy, server? Is it unavoidable?
- Model routing: Can you restrict which models are allowed by group, project, or data class?
- Tool access: Are tool/function calls permissioned per tool and per action (read vs write)?
- Data classes: Can customers mark inputs/outputs as public/internal/restricted and enforce routing rules?
- Override path: Is there a break-glass process with extra logging for exceptions?

3) AUDIT & TRACEABILITY
- Who did what: Can you attribute each request and tool action to a user identity and workspace/project?
- What happened: Do you record model name/version, parameters, tool calls, and failure modes?
- Export: Can audit logs be exported to customer systems (SIEM/log pipelines) without bespoke work?
- Retention: Are retention controls explicit and configurable?

4) COST CONTROL (AI FINOPS BASICS)
- Budgeting: Can customers set budgets by team, project, and environment (dev/staging/prod)?
- Rate limits: Can you enforce limits per key/user/service to prevent runaway usage?
- Caching: Do you support deterministic caching options where appropriate (and safe)?
- Attribution: Can you map spend to product endpoints/features, not just “total tokens”?

5) RELIABILITY & RESILIENCE
- Timeouts/retries: Are timeouts sane and retries bounded?
- Fallbacks: Can you fail over across model providers or model tiers for critical paths?
- Degradation: What happens when AI is down—does the workflow fail gracefully?
- Incident response: Do you have a documented incident process and status communication?

6) DEPLOYMENT & DATA BOUNDARIES
- Connectivity: Can you support private connectivity patterns customers expect (at minimum, clear options)?
- Secrets: How are API keys and credentials stored, rotated, and scoped?
- Egress: Can customers control outbound network access for tool calls?

PASS/FAIL RULE
If a customer asked you to roll out to a regulated team tomorrow, could you: (1) enforce who can use what model, (2) prove what the AI did, (3) cap spend, and (4) survive an upstream outage? If any answer is “not really,” your roadmap is clear.