The business case for AI automation using Azure Functions

I’m designing AI automation for advice firms that runs on Azure Functions — and the economics are better than many realise.

Azure Functions’ consumption plan includes a monthly free allocation of 400,000 GB-seconds and 1 million executions. For many firms, that’s enough to run powerful automation without leaving the free tier.

Here’s an example of what comfortably fits within that free allocation (assuming a 512 MB function size):

Document intelligence

Process 10,000 client documents monthly (redaction, OCR, classification, data extraction) at 8 seconds each → 40,000 GB-seconds

Compliance monitoring

Run 2,500 automated compliance checks (using a detailed, multi-pass LLM analysis) at 10 seconds each → 12,500 GB-seconds

Report generation

Auto-generate 5,000 client review summaries, portfolio reports or meeting-prep documents at 10 seconds each → 25,000 GB-seconds

That’s three advanced automation processes for an advice firm at useful scale — for less than 20% of your free allocation.

Other costs to factor in

There are other costs to factor in:

• AI model tokens (say Azure OpenAI GPT-4.1 or equivalent): scales linearly with usage; typically a few hundred dollars a month at this scale.
• Data storage: usually modest — many automations simply read from and write back to your existing document store or CRM.
• Secure key storage, logging and monitoring: minimal cost, but worth noting.

All up, we’re talking a few hundred dollars a month to run serious AI-powered automation, not tens of thousands.

And because most firms already run on Microsoft 365, this design simply extends use of that trusted ecosystem.

It takes a bit of creative thinking and a willingness to learn these lightweight technical patterns, but AI assistance makes that journey easier than ever.

I’m excited that firms aren’t just open-minded to this kind of thinking — they’re rolling up their sleeves and getting started. 🙂 💪