Stop Asking What AI Can Do. Ask What Your Staff Hates to Do.

Ask a small business owner if they use AI and most say yes. Ask what they use it for and you hear the same short list: write an email faster, clean up a document, draft a caption. That's real, and it's useful. It's also a tiny fraction of what the tool in front of them can do.

On a recent episode of the Small Business, Big AI podcast, Pivot180 founder and CEO Brandon Hurter joined host Kim to talk through what the next step looks like: not the theory of AI for small business, but the deployment of it. The part where it has to work on a Tuesday for a real company with a number attached. This post is the short version of that conversation. You can listen to the whole thing below.

Listen to the full episode

Stop Asking What AI Can Do. Ask What Your Staff Hates to Do.

Brandon Hurter on Small Business, Big AI·Audio

Pivot180 founder Brandon Hurter joins Small Business, Big AI to talk through how small and mid-sized businesses put AI to work, one workflow at a time. He covers a real law-firm deployment that turned a $12,000 build into $350,000 a year in savings, the five questions to answer before you buy anything, and the crawl, walk, run approach that lets each workflow pay for the next.

The gap isn't access. It's knowing what to point it at.

Almost everyone has access to capable AI now. That's not where businesses get stuck. They get stuck knowing what to aim it at. Most owners stop at using AI to generate content. Few make the jump to the next evolution, which is here today: automating a multi-step job that a staff member does over and over.

Think about the report someone runs every Thursday: pull data from three systems, drop it into a clean presentation, then double- and triple-check it before it goes to the CEO or the board. That's two to four hours, every week, that people quietly dread. The next evolution is turning that four-hour Thursday job into a four-minute one, which frees that person up for higher-value work.

The question that surfaces the real work

Ask an owner "where is your process friction?" and their eyes glaze over. Ask "what is the one thing your staff hates to do?" and they can answer instantly. Everyone knows the task their team groans about every week.

Take a landscaping crew. After every job, the field team sits in the truck writing up the invoice, building the next estimate, and texting the next customer that they're on their way. That's 40 minutes a stop pulled away from the real work, and the owner may not even know the friction exists unless someone complains. Naming the thing people hate is the fastest way to find the workflow worth automating.

A real deployment: $12,000 in, ~$350,000 a year out

Pivot180's first client was a law firm in Raleigh, North Carolina. Their core system, Filevine, holds every client's data, case documents, and communications. The problem: a team of eight paralegals and their manager were collectively spending roughly 25 to 50 hours a week doing manual work inside that system: uploading and downloading documents, tagging clients to the right case, and writing and sending communications. That's time the paralegals should have been spending supporting the attorneys.

We documented what the paralegals did, then built AI agents with API access into Filevine to do those defined jobs. The first two workflows:

• Client communications. When a client onboards to the portal, an email now goes out automatically with a welcome and the next steps. That used to be a paralegal copying the right message out of a Word doc in SharePoint, pasting it into Filevine, and hitting send.
• Proof-of-validation review. New clients upload proof they're eligible to be a plaintiff: an invoice, a screenshot of an account number, and the like. A model now inspects each document against the firm's rubric (is it high enough resolution, does it have the right information, is it legally valid?) and recommends approve, reject, or send-to-manual-review, each with a confidence score. The attorney keeps the final say. It wakes up on every new upload and cleared a backlog of tens of thousands of documents.

Those two workflows cost roughly $10,000 to $12,000 to build, deploy, and get right. Over the course of a year, the saved hours add up to somewhere near $300,000 to $350,000. It's an unglamorous workflow, the exact thing the team complained about, and that's the point. One workflow, fixed once, that paid for itself.

Five questions to answer on a legal pad

You don't need to buy anything to start. Take 20 minutes and answer these five. They're a subset of the questions we walk through with clients:

1. Where is the work repetitive?
2. Where does communication break down, internally (dispatch, handoffs) and externally (clients, patients, customers)?
3. Where do customers or clients wait? (Your worst Google reviews are a good place to look.)
4. What eats staff time without needing real judgment?
5. What does your team hate to do?

Write those down and you've mapped the workflows worth examining, and probably automating.

Three paths to your first workflow

1. Use what you already own. If you run Google Workspace or Microsoft 365, you already have Gemini or Copilot. Many businesses don't realize the capability is already sitting in the tools they pay for, which is the lowest-cost place to start.
2. A vertical tool built for your industry. Generic models are trained on a broad public corpus. Landscaping isn't HVAC isn't a law firm. Where a tool exists that's purpose-built for your business, pilot it.
3. A custom build. When there's no internal capability and no vertical fit, a custom workflow can be built for a fraction of what most owners expect.

The failure mode to avoid: AI sprawl

When AI projects go wrong, it's usually not the technology. It's the preparation. An owner buys the tool a competitor mentioned at a conference without understanding how that job is done by people today, then bolts it on top of the business. The result is a pile of siloed, single-purpose tools that create more work to manage than they ever removed. The old idea of "IT sprawl" is alive and well in AI. Understand the workflow first; buy second.

Crawl, walk, run

You don't need a transformation. You need one workflow: build it, get comfortable with it, and let the value it returns fund the next one. The businesses tinkering today, one workflow at a time, will be well ahead of the ones still waiting for a grand plan. If you feel a step behind, you're not alone; almost everyone is at the start of this. The move is to pick the thing your team hates and go.

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