Executive Checklist (10 Questions)

The following 10 questions assess whether an organization possesses the strategic and execution readiness for AI-native infrastructure. The diagram below categorizes these questions into three domains: strategy, governance, and execution, facilitating executive discussions.

Figure 1: Executive checklist structure diagram

Can you clearly define the unit cost for each major AI workload (e.g., per 1M tokens, per agent task, per batch job)?
Do you have budget/quota mechanisms that can constrain team/project/tenant compute consumption within controllable bounds?
Can you make explicit policy trade-offs between “performance (throughput/latency)—cost—risk” (rather than relying on verbal constraints)?
Can your platform handle uncertainty: spikes, long-tail effects, and resource fluctuations caused by agent path explosions?
Are agent/MCP “intents” mapped to actionable and billable/auditable resource consequences?
Do you have clear resource isolation and sharing strategies (same-card sharing, memory isolation, preemption, prioritization) to improve utilization?
Can you achieve cross-layer observability: end-to-end tracing from request/agent → runtime → GPU/network/storage → cost?
Does your infrastructure support rapid adoption of new hardware/interconnect/topology changes (heterogeneity and evolution are the norm)?
Has the organization established “AI SRE/ModelOps + FinOps” collaboration mechanisms and accountability boundaries (who owns cost and reliability)?
When you say “we are AI-native,” can you provide three planes + one closed loop architecture diagram and governance strategy on a single page?

References

Created on Jan 18, 2026 Updated on Jan 18, 2026 227 words about 2 Minute