FinOps for the AI Era
Source-grounded pack with Map AI Cost and Ownership, Govern AI Spend Without Policing, and Build an AI FinOps Optimization Backlog, plus 1 more.
Use this pack when
Choose this pack when the work touches FinOps for the AI Era and you need a bounded workflow with explicit inputs, a defined output, and human review gates.
Included workflows
Choose the job in front of you.
4 source-grounded skills. Load one workflow at a time.
Map AI Cost and Ownership
Use this workflow when inventorying and allocating company-wide AI spend across infrastructure, product inference, internal tools, agents, data preparation, evaluation, vendors, and human support so cost has owners and business meaning.
Output Return an aispendmap with costsurfaces, items, tags, allocationrules, owners, costclass, usage, valuehypothesis, risk, renewals, overlap, unallocated, evidencegaps, and showbackviews.
Govern AI Spend Without Policing
Use this workflow when governing AI tools, models, product features, and agents with risk-based tiers, approved paths, owners, budgets, anomaly controls, structured experiments, vendor lifecycle, and useful review cadence without creating an AI police function.
Output Return an aispendgovernancebrief with tiers, approvedpaths, owners, budgets, agentcontrols, anomalies, experimentrules, vendorlifecycle, exceptions, embeddedcontrols, and reviewcadence.
Build an AI FinOps Optimization Backlog
Use this workflow when turning AI spend, quality, and value evidence into a recurring optimization portfolio across routing, context, caching, retries, batching, licenses, vendors, agents, architecture, commitments, pricing, and retirement.
Output Return an aifinopsbacklog with opportunities, baseline, lever, expectedimpact, qualityguardrail, latencyguardrail, effort, risk, dependencies, priority, owner, acceptance, rollback, and reali
Review AI Unit Economics
Use this workflow when testing the P&L and scaling economics of an AI product, internal workflow, agent, or premium-model tier using full cost per successful outcome, customer or cohort profitability, routing, packaging, and adverse usage scenarios.
Output Return an aiuniteconomicsreview with outcomeunit, fullcost, segments, margin, routingoptions, premiumlift, contextpolicy, pricingoptions, scenarios, sensitivity, decision, and gates.
Human review
Keep consequential decisions explicit.
These workflows structure analysis and artifacts; they do not authorize autonomous external, personnel, financial, legal, security, or other high-impact action.
Source and files
Grounded in the complete FinOps for the AI Era series.
10 source essays · 4 usable skills · reviewed Jul 2026