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Track the economics of AI usage, from token accounting to cost per completed task. Connect spending to engineering outcomes rather than treating usage as value.
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80 termsAI avoided cost
AI avoided cost is expense reduced or prevented compared with a credible alternative. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI batching savings
AI batching savings is reduction in effective cost or overhead from processing eligible work in batches. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI benefit realization
AI benefit realization is verification that expected AI benefits occurred in operations. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI break-even volume
AI break-even volume is workload volume where AI benefits equal operating and investment costs. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI budget alert
AI budget alert is a notification triggered by a consumption or spend threshold. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI budget owner
AI budget owner is the person or team accountable for an AI spending limit. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI budget variance
AI budget variance is the amount actual AI spending differs from an approved budget. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI business case
AI business case is a structured argument for funding AI with costs, benefits, risks, and measures. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI chargeback
AI chargeback is a policy that bills an internal consumer for its AI resources. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI cost attribution
AI cost attribution is the process of assigning AI expense to a responsible business dimension. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI cost center
AI cost center is an accounting boundary used to collect and manage AI-related expense. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI cost of goods sold
AI cost of goods sold is direct AI expense required to deliver a sold product or service. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI failure cost
AI failure cost is cost of model work ending in an error, abandonment, or unusable result. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI governance cost
AI governance cost is expense of controls, review, monitoring, documentation, and oversight. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI incremental revenue
AI incremental revenue is additional revenue plausibly attributable to an AI-enabled capability. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI net present value
AI net present value is present value of expected AI cash flows minus investment and operating costs. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI opportunity cost
AI opportunity cost is value of the best alternative use of money, people, or capacity. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI payback period
AI payback period is time for cumulative AI benefits to recover investment cost. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI price-performance ratio
AI price-performance ratio is useful performance delivered for a given model cost. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI productivity value
AI productivity value is measurable value created when AI changes useful work volume, speed, or quality. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI retry cost
AI retry cost is additional model expense caused by repeating a request or workflow step. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI ROI attribution
AI ROI attribution is connecting measured benefits and costs to a particular AI capability. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI ROI baseline
AI ROI baseline is the documented starting point used to compare an AI investment. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI ROI confidence
AI ROI confidence is a statement of how certain an AI return estimate is and why. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI scenario analysis
AI scenario analysis is comparison of distinct future operating cases for an AI workload. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI sensitivity analysis
AI sensitivity analysis is testing how an ROI estimate changes when assumptions move. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI showback
AI showback is a transparent report of AI consumption and cost without an internal transfer. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI spend forecast
AI spend forecast is an estimate of future AI expense using usage, price, and workload assumptions. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI spend forecast error
AI spend forecast error is the difference between projected AI spend and incurred expense. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI time saved
AI time saved is working time avoided or redirected by an AI-assisted workflow. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI total cost of ownership
AI total cost of ownership is the full cost of operating AI across providers, infrastructure, people, integration, and governance. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI usage attribution
AI usage attribution is the practice of assigning requests and tokens to people, products, or workflows. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIAI volume discount
AI volume discount is a price reduction tied to reaching a stated usage level. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIBlended AI rate
Blended AI rate is an average rate combining models, token classes, or pricing tiers. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICached token ratio
Cached token ratio is the share of input tokens served from a reusable context cache. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICommitted use discount
Committed use discount is a lower effective rate offered for a usage or capacity commitment. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROIContext overhead
Context overhead is tokens carrying history, retrieved material, tools, or metadata around a task. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per agent run
Cost per agent run is model expense incurred by one execution of an agent task. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per AI evaluation
Cost per AI evaluation is expense of evaluating one response, task, or candidate system. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per AI review
Cost per AI review is the model expense required to produce one code or document review. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per AI session
Cost per AI session is the average AI expense associated with one user or agent session. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per AI test run
Cost per AI test run is model expense for generating, selecting, or analyzing one test run. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per AI user
Cost per AI user is the average AI expense associated with a user over a period. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per AI workflow
Cost per AI workflow is the average model expense for one defined multi-step workflow. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per code change
Cost per code change is AI expense associated with producing a code change that reaches an agreed state. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per completed task
Cost per completed task is the total cost of attempting a workload divided by the number of tasks that meet its completion criteria. For AI workflows, it can include model calls, retries, tool execution, and other costs within the stated measurement boundary.
Token costs and AI ROICost per generated artifact
Cost per generated artifact is the average expense for one accepted patch, summary, or report. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per resolved issue
Cost per resolved issue is model spend associated with resolving one software or support issue. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per successful AI outcome
Cost per successful AI outcome is the AI expense required for an agreed successful result. It gives teams a way to name, measure, or reason about an economic property of an AI workload without treating raw usage as proof of value.
Token costs and AI ROICost per token
Cost per token is the price charged for processing a defined number of input or output tokens. Providers commonly quote separate input and output rates, and some offer lower prices for cached or batched work.
Token costs and AI ROI