Reports/AI Cost Management Report

IFO4 Research

AI Cost Management Report

Navigating the Economics of Enterprise AI

February 2026|86 pages|premium

Executive Summary Preview

Enterprise AI adoption has reached an inflection point where cost management can no longer be an afterthought. AI-related cloud spending is projected to reach $142B annually, yet our research reveals 38.2% of this spend is waste.

GPU utilization across enterprise deployments averages just 34%, with idle inference endpoints and over-provisioned training clusters as the primary waste sources.

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Table of Contents

Executive Summaryp. 1

AI Spend Landscapep. 6

GPU Cost Analysisp. 18

Model Training Economicsp. 34

Inference Cost Optimizationp. 48

AI Waste Patternsp. 58

Recommendationsp. 72

Appendixp. 80

Key Findings

38.2%

AI waste rate at 38.2%

Higher than overall cloud waste (27.3%), driven by idle GPU instances and over-provisioned inference endpoints.

34%

GPU utilization averages 34%

Most GPU instances spend majority of time idle. Auto-scaling adoption remains below 20%.

28%

Organizations with AI FinOps save 28% more

Dedicated AI cost management teams deliver significantly better optimization outcomes.

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86 pages of in-depth analysis, data tables, and actionable recommendations.

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