A Practical Guide to AI Automation for Small Teams

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Every week I talk to founders who think AI automation requires hiring ML engineers and building infrastructure. It doesn't. Here's what actually works for teams of 2-10 people.

Start With Your Worst Process

Don't start with "how can we use AI?" Start with "what's our most painful manual process?" For most small teams, it's one of:

  • Document processing (invoices, contracts, intake forms)
  • Customer support triage
  • Data entry between systems
  • Report generation

Pick one. Just one.

The Stack That Works

For document processing, you need three things:

  1. A document parser — extract text from PDFs, images, forms
  2. An LLM — structure the extracted text into your data model
  3. A connector — push the structured data to your system of record

That's it. No vector databases, no fine-tuning, no RAG pipelines.

When to Level Up

Add complexity only when simple doesn't work. Most automation projects fail because they start complex, not because simple wasn't enough.

If your document types vary wildly, add a classifier. If accuracy matters, add validation. If you process thousands daily, add queue management. But start with the simple version first.