Is Your Company Overpaying for AI? A 15-Minute Audit That Could Save You Thousands
The average business spends $100-5,000/month on AI tools. Most are using premium models for tasks that a $0.30/M token model handles just fine.
A fintech startup I advise was spending $2,300/month on AI tools. After a 15-minute audit, we cut it to $890 — a 61% reduction — with zero impact on output quality. Their mistake was common: they were using Claude Opus ($75 per million output tokens) for customer support ticket classification — a task that Gemini Flash ($0.30 per million tokens) handles with 99% of the same accuracy.
This pattern repeats everywhere. The model that gives you the best results isn't always the model you need.
The 3-Question Audit
Go through every AI tool your company pays for and ask these three questions:
1. What tasks is this tool actually being used for? (Not what you bought it for — what people actually do with it day-to-day.)
2. Does this task require frontier-model quality, or would a cheaper model work? Classification, routing, simple summarization, and data extraction rarely need Opus or GPT-5.4. Test with a cheaper model before assuming you need the premium one.
3. Are there overlapping tools? If you're paying for ChatGPT Plus AND Claude Pro AND Gemini Pro, that's $60/month for three chatbots. Most people primarily use one. Cancel the other two.
In my experience, Question 2 is where the biggest savings hide. Teams default to the most powerful model because it feels safer. But for 70-80% of business tasks, the gap between a $3/M model and a $75/M model is imperceptible.
The Model Routing Playbook
Here's how to match model to task for maximum savings:
The key insight: reserve expensive models for tasks where errors have consequences. Customer support? A wrong answer gets corrected by a human. Legal analysis? A wrong answer could cost millions. Price your AI according to the cost of failure, not the cost of the model.