What Practical AI Consulting Looks Like

Practical AI consulting isn't what most firms sell

Most AI consulting engagements look like this: a discovery phase, a strategy deck, a roadmap, a phased implementation plan, and a statement of work that runs six figures before anyone writes a line of code.

That's not practical. That's consulting theater.

Practical AI consulting starts with a different question: *what workflow is costing you the most time right now?*

Not "what is your digital transformation strategy?" Not "how does AI fit into your five-year roadmap?" Just: what's the thing your team does every day that they hate doing, that takes too long, that produces inconsistent results?

That's where we start.

What practical looks like in the real world

Here's a pattern I see constantly with Indiana small businesses:

A 12-person company has one person whose job is copying information between systems. Form submission into a CRM, CRM into an invoice, invoice into a report. Six hours a day. Not strategic work. Transcription.

Practical AI consulting means: build something that does that in fifteen minutes, test it with the person who does the job, measure whether it holds up on a Tuesday morning, and hand it off.

That's it. The engagement is four to six weeks. The output is working software. The measurement is time saved.

The difference between practical and theoretical AI consulting

Theoretical AI consulting produces: - Strategy frameworks - Maturity assessments - Vendor comparison matrices - Implementation roadmaps - Steering committee presentations

Practical AI consulting produces: - A working prototype in week two - A tested version by week four - A handoff with documentation - A clear answer to "did this work?"

I'm not saying strategy is worthless. Most small businesses don't need a strategy. They need one thing fixed.

Why Indianapolis businesses are a good fit for this approach

Indiana businesses tend to be pragmatic. They've watched the tech hype cycles come and go: blockchain, VR, the metaverse. They're not interested in being early adopters for its own sake. They want to know if it works.

That's the right mindset for practical AI consulting. The question isn't "should we use AI?" The question is "does this specific thing solve this specific problem?"

When the answer is yes, we build it. When the answer is no, I'll say that too.

What I do

I work with Indiana businesses on four types of problems:

Workflow automation: repetitive processes that eat time. Document processing, data entry, report generation, approval routing.

AI phone agents: handling inbound calls for appointment scheduling, intake, FAQ, after-hours coverage. Built on real phone infrastructure, not chatbot demos.

Cash flow audits: finding where time is bleeding out of the business. Often the most valuable first step before any implementation.

Custom AI tools: internal knowledge bases, draft generation, QA automation, anything that uses your data to make your team faster.

First projects run four to six weeks. Budget is $5k to $25k depending on complexity. No retainers until we've shipped something together.

How to know if you're ready

You're ready for practical AI consulting if you can answer this: *what's the workflow that costs us the most time every week, and who owns it?*

Name the workflow and name the person. That's enough to get started. If the answer is "we need to figure out our AI strategy first," you probably need a different conversation.

Let's talk about your workflow

---

*Bracken Fields is an AI consultant based in Indianapolis. He's spent 20 years building software for contact centers and SaaS companies. He helps Indiana businesses implement AI that works.*