Benchmarking

How Much Is Your Company Actually Spending on AI? A Benchmarking Guide

How Much Is Your Company Actually Spending on AI? A Benchmarking Guide
Usagely Team

Usagely Team

April 17, 2026

7 min read

The Hidden Cost of AI Adoption

AI tools have become essential for modern engineering teams. But most companies have no idea how much they're actually spending.

Here's a typical scenario: an engineering manager discovers the team is spending $80,000 per month on AI tools — found out from the credit card statement.

AI Spending Benchmarks

Based on industry data and Usagely's analysis of engineering organizations:

| Company Size | Avg AI Tools | Monthly Spend | Per Developer | |---|---|---|---| | 10-50 engineers | 5-8 tools | $5K-$20K | $200-$500 | | 50-200 engineers | 8-12 tools | $20K-$80K | $300-$600 | | 200-1000 engineers | 12-20 tools | $80K-$300K | $400-$700 | | 1000+ engineers | 15-30 tools | $300K+ | $300-$600 |

Where the Money Goes

API-Based Tools (Usage Pricing)

  • OpenAI API: $0.15-$60 per million tokens depending on model
  • Anthropic API: $0.25-$75 per million tokens
  • AWS Bedrock: Varies by model, plus AWS markup
  • Google Vertex AI: Competitive with direct pricing

Seat-Based Tools (Per-User Pricing)

  • GitHub Copilot: $10-$39/user/month
  • Cursor: $20-$40/user/month
  • ChatGPT Team: $25-$30/user/month
  • Claude Pro/Team: $20-$30/user/month

Hidden Costs

  • Duplicate seats: Same developer on Copilot AND Cursor AND Claude Pro
  • Unused API keys: Keys that continue generating costs after projects end
  • Shadow AI: Tools purchased on personal cards or free tiers with usage limits
  • Model over-selection: Using GPT-4 when GPT-4o-mini would suffice

How to Audit Your AI Spending

  1. Inventory all AI tools — Check expense reports, SSO logs, and browser histories
  2. Categorize by type — API-based vs. seat-based vs. free-tier
  3. Map to users — Who uses what, and how often?
  4. Calculate cost per outcome — Cost per PR merged, per feature shipped, per support ticket resolved
  5. Identify waste — Duplicate tools, unused seats, over-powered models

The 20-40% Waste Factor

Studies show that 20-40% of AI budget is wasted on:

  • Duplicate tools serving the same purpose
  • Over-provisioned seats for users who barely log in
  • Unoptimized model selection (expensive models for simple tasks)
  • Shadow AI tools that duplicate licensed alternatives

For a company spending $50K/month on AI, that's $10K-$20K in potential savings.

Benchmark Your Team with Usagely

Usagely gives you instant visibility into every AI tool, model, and user — with savings recommendations ranked by confidence and effort. Connect your providers and see where you stand in under 5 minutes.