What is an AI Efficiency Score?
An AI Efficiency Score is a 0-100 metric summarizing how efficiently a company's AI spend is being used, based on waste, attribution coverage, and budget compliance.
An AI Efficiency Score is a single 0-100 metric that summarizes how efficiently a company is using its AI API spend, combining factors like waste percentage, attribution coverage, and budget compliance into one board-reportable number.
Why a single score is useful
Engineering and finance teams often need one number to track over time and report to leadership, rather than a dashboard full of granular metrics. A single efficiency score, tracked quarter over quarter, shows whether AI spend management is improving.
What typically factors into an AI Efficiency Score
Percentage of spend classified as waste, percentage of API calls with attribution tags, adherence to configured budgets, and cost trend direction.
How Cognocient calculates its AI Efficiency Score
Cognocient calculates this score directly from actual account usage (not a self-reported survey), maps it to the FinOps Foundation's Crawl/Walk/Run maturity model, and shows exactly what action would move the score to the next tier. See it as the FinOps Maturity Score in your dashboard.
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Related: Cost per outcome · AI spend attribution · FinOps Maturity Score
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AI FinOps Glossary
Definitions for AI spend management terms: token maxing, context tax, cost per outcome, AI spend attribution, and more.
What is Token Maxing?
Token maxing is the practice of using expensive frontier AI models for tasks that cheaper models handle equally well.
What is Context Tax?
Context tax is the recurring cost of sending a large, mostly-static system prompt with every API call.