What AI Consulting Actually Costs (And Why Most Firms Won't Tell You)

Why Nobody Will Give You a Number

Try to find out what AI consulting costs and you will hit the same wall everywhere: “contact us for pricing.” The standard defense is that every engagement is different, and there is some truth in that. But the fuller truth is less flattering. Hidden pricing lets a firm quote what it thinks you can pay rather than what the work is worth. It protects rate cards that would embarrass the seller if printed next to the deliverables. And it filters for buyers too large or too rushed to comparison-shop — which is precisely why the firms serving the biggest clients hide their numbers most aggressively.

I run Interactive Intel, a Miami-based AI consulting boutique, and we publish our engagement prices on our website. Not because we are saints — because opaque pricing wastes my time as much as yours. Every hour I spend in a pricing dance with a prospect who needed a $12K audit, not a $200K transformation, is an hour neither of us gets back. So let me do here what most of the industry will not: walk through real numbers, what they include, and what makes them move.

The Three Bands We Publish

The auditis the diagnostic tier. In two to three weeks we document your core processes, assess the actual state of your data, and hand you a written report naming the highest-leverage workflow to automate first. Sometimes the finding is “not yet, and here is what to fix first” — which, at $5K–$15K, is the cheapest version of that lesson you will ever buy.

The sprintis our flagship because it matches how AI value is actually created at growth-stage scale: one workflow, one agent, in production. Over six to ten weeks you get the agent built on a modern stack — we work with Anthropic's Claude, OpenAI, Next.js, Supabase, and the integration layers your business already runs on — wired into your real systems, tested against real cases by the people who will use it, and handed over with documentation. Not a prototype, not a deck. Production software.

The enterprise tier exists for organizations where one workflow is never just one workflow — multiple locations, regulated data, several systems of record. It is by invitation because programs at that scale only succeed with genuine executive commitment, and we would rather decline an engagement than preside over a stalled one.

What Moves the Number Up or Down

Within each band, three variables do almost all the work. Scopeis the obvious one: an agent that triages inbound email is a smaller build than one that triages, drafts responses, books appointments, and updates three systems. The discipline that keeps sprints near the bottom of the band is ruthlessly cutting the first version to the workflow's core — you can always extend a working agent; you cannot rescue an overscoped one.

Data readinessis the silent multiplier. If your customer records are structured and your processes are documented, the build moves fast. If the agent's inputs live in free-text fields, staff memory, and a legacy system that exports ambiguity, weeks of the budget go to cleanup before a line of agent logic is written. This is why we audit before we build: it converts the biggest unknown in the price into a known.

Integrations are the third lever. Modern APIs — Stripe, a well-documented CRM, a standard calendar — are cheap to connect. Healthcare interfaces like FHIR and HL7, legacy systems with no API, or anything requiring a security review add real cost, and any firm quoting you a flat price without asking what your agent must talk to is guessing.

What a Sprint Looks Like From the Inside

A concrete example from my own delivery work. A Florida SaaS company — seed to Series A stage, the size where every hire is felt — came to us with the classic growth-stage problem: a workflow eating senior time that no one could justify hiring against. We ran it as a textbook sprint: one workflow, one agent, production in ten weeks. The first weeks went to scoping and to the unglamorous work of pinning down how the process actually ran versus how everyone described it. The middle weeks were the build and integration. The final weeks were testing against real cases with the team that owns the workflow, then deployment and handover. That cadence — and the restraint of not bolting on “just one more thing” mid-build — is what keeps a sprint inside its band.

I will add that we eat our own cooking. Interactive Intel itself runs on agentic AI — our lead intake scrapes and structures inbound email, an agentic assistant handles client onboarding, our proposals are automated, and this website was rebuilt with Claude Code. When I estimate a build, I am estimating work I do in my own firm every week, not work I will hand to a delivery team I have never met.

Big Four vs. Boutique vs. Platform Vendor

Where do these numbers sit in the wider market? When we researched our own positioning, three tiers emerged. At the top, the global consultancies — the Big Four and the major strategy houses — generally will not take a meeting for an AI engagement under roughly half a million dollars. Their model needs leverage: a partner sells the work, and a pyramid of junior consultants delivers it. If you are a mid-market company, you are not their customer, whatever the pitch deck implies.

At the bottom sits the freelancer and offshore market, where pricing is attractive and quality is genuinely uneven — some excellent independents, and a great deal of prompt-wrapping sold as engineering, with no accountability when the agent meets a real edge case. The risk is not paying too much; it is paying twice.

In between are operator-led boutiques, and here I will state our own case plainly, as the conclusion of our market research rather than neutral fact: senior-led boutiques deliver comparable outcomes at 30–40% lower cost than the large firms, because you are paying for the practitioner's time instead of a brand premium and a pyramid. The person who scopes your engagement builds it. Whether that boutique is us or someone else, the structural argument holds — and it is exactly why the big firms keep their prices off the page.

How to Evaluate ROI Before You Sign

The price only matters relative to the return, so do this arithmetic before signing anything. Take the workflow in question and put real numbers on it: hours per week it consumes, the loaded cost of the people doing it, and the revenue cost of its failures — the lead that went cold overnight, the booking that fell through, the proposal that went out late. To keep the math illustrative: a workflow consuming twenty hours a week of staff time at $50 loaded cost is roughly $50K a year before you count a single lost lead. Against a $25K–$60K sprint, the payback question stops being abstract — it becomes “do I believe the agent can take over most of this workflow?”, which is a question a good audit answers with evidence.

Then hold whoever you hire to three contractual tests: a fixed scope in writing (one workflow, named integrations, a defined “done”), a production deliverable rather than a recommendations deck, and a measurement plan that compares the workflow's before-and-after numbers. Any firm that resists all three is selling you hours, not outcomes.

If you want to run your own numbers first, we built a free ROI calculator on our homepage — plug in your workflow's hours and costs and see what automation is worth to you before you talk to anyone, including us. And if the numbers look interesting, book a call. You will be talking to me, the prices are the ones above, and if your situation calls for a $5K audit rather than a $60K sprint, that is exactly what I will tell you.