Seven questions to ask on the first call, three of which a reseller cannot answer, and the four situations where the honest recommendation is to not hire anyone yet.
Part of our guide to AI enablement for small business.
You are about to spend somewhere between $3,500 and $180,000 on help you cannot evaluate yet. That is the actual problem with hiring an AI enablement company. The category is two years old, the credentials are unverifiable, and every firm on page one of Google describes itself in the same four words: readiness, governance, adoption, scale.
Harvard Business Review puts the number of AI projects that never reach full deployment at roughly 80%. Most of those did not fail on the technology. They failed because nobody changed how the work actually gets done, and the vendor was never on the hook for that part.
So this guide is built to be used against us as much as for us. Below are the seven questions that separate a firm that runs AI systems from a firm that resells licenses, how to score the answers on a live call, what the work costs when someone publishes a real number, and the four conditions where you should not hire anybody, including WE•DO.
What an AI Enablement Company Is Actually Supposed to Do
AI enablement is the work of connecting AI to a job your business already does, with an owner, a review step, and a place the output lands. It is not tool selection. It is not a training session. It is the wiring between a tool you probably already pay for and a workflow that currently runs on somebody's Tuesday.
The distinction matters because the license is the cheap part. You can buy seats for a twenty-person team this afternoon. What you cannot buy this afternoon is the decision about which of your recurring jobs goes first, what the model is allowed to touch, who reads the output before a client does, and what happens when the workflow breaks in month four.
A good enablement partner arrives at that conversation with opinions. A weak one arrives with a platform.
Enablement, Consulting, Agency, or Reseller: Know Who You Are Talking To
Four different business models use nearly identical language. Figure out which one is on the call before you compare prices, because you are otherwise comparing a strategy document to a working system.
None of these is illegitimate. A reseller is a fine purchase if what you need is seats. The failure happens when you buy seats and expect the operating change. If the work you are buying is campaign execution rather than operations, that is a different comparison, and we wrote it up separately in what an AI marketing agency actually does.
The Seven Questions
Ask all seven on the first call. Numbers two, five, and seven are the ones that cannot be answered from a deck, and the stall you hear is the answer.
01. Which workflow changes first, and on what date?
A serious answer names the job, the trigger, and roughly when it goes live: "Your weekly client reporting, triggered every Monday off the GA4 pull, drafted by day 21." A weak answer names a phase. If the first deliverable is a discovery readout with no build attached, you are buying a document. Our own version of that sequencing decision is written up in the AI enablement framework.
What good sounds like: they ask which job eats your team's week before they say a single tool name.
02. Show me what you run on yourselves
This is the one that ends calls. Ask them to screen share an AI workflow their own company depends on, right now, in the meeting. Not a client case study. Not a demo environment. The thing they would notice was broken by Thursday.
A firm that has built for itself will show you something unglamorous, because real internal systems are unglamorous. A firm that has not will offer a case study instead. That is not automatically disqualifying, but it tells you exactly who will be learning on your budget.
Why it works: nobody can fake an internal system live. It either exists or it does not.
03. What does the build cost, and what does it cost to keep running?
Two numbers, and most quotes only carry one. The build fee is easy. The run rate is the model and API usage, the per-seat licenses, and the hours somebody spends when the workflow breaks. A $12,000 build with a $900 a month run rate is a different decision than a $12,000 build with a $90 a month run rate, and you should not discover which one you bought in month four.
04. Who reviews the output before a customer sees it?
The answer has to be a role, not a hope. "The team will check it" is not ownership, and it is the single most common gap between a workflow that survives and one that gets quietly turned off after an embarrassing send. Ask them to write the review gates into the scope of work: what ships without review, what needs a human pass, and what AI is not allowed to touch at all.
05. What will you refuse to automate for us?
Every operator who has actually shipped this work has a list. Ours includes anything where a wrong answer costs a client relationship, anything requiring judgment about a person, and pricing decisions. A vendor with no list has either never hit the wall or is optimizing for scope, and both of those get expensive.
What good sounds like: they volunteer the list before you ask, and they can tell you the incident that put an item on it.
06. What do we own when you leave?
Get this in writing before kickoff: the accounts and API keys in your name, the prompts and system instructions in your documentation, the workflow map, and a named internal owner who has run it at least twice without help. If the workflow only runs while the invoice does, you did not buy enablement. You hired an operator.
07. What number moves by day 90, and what happens if it does not?
Ask them to commit to one metric before the contract is signed: hours returned per week, error rate, response time, output per person. Then ask the harder half of the question, which is what they do if the number holds flat. A firm that has run enough of these has an answer, usually some version of "we rebuild the lane at no cost or we tell you to stop." A firm that has not will tell you AI takes time.
Any vendor can answer questions one, three, four, and six from a template. Two, five, and seven require having done the work.
How to Score What You Hear
You are not grading enthusiasm or polish. You are checking for one thing: does anything specific happen after the contract is signed?
One more filter that costs you nothing. Before the call, search the firm's site for a price. Not a range in a PDF you have to trade an email for, an actual number on a page. Almost nobody in this category publishes one, and the ones who do have usually scoped the work enough times to know what it takes.
What It Actually Costs
Enterprise AI enablement engagements run $200,000 to $500,000 over 12 to 18 months. If you run a company with 5 to 100 people, that is not your engagement, and any firm quoting you that shape of program is selling you a governance framework you will never staff.
Here is the honest read on those tiers. The audit is worth it only if you genuinely do not know which job to start with, and most owners do know. The focused engagement is where the actual return lives, because one live workflow with an internal owner is what makes the second one cheap. The monthly tier makes sense once you have proven a lane and want three more. Our own scope and pricing for each of those sits on the AI integration services page.
Whatever you pay, hold the vendor to a comparison against the alternative: what would it cost to hire a person to do this job, and what would it cost to keep doing it by hand for another year? If the enablement work cannot beat both, do not buy it.
When Not to Hire Anyone
This is the section most firms leave out, which is why it is the most useful one. There are four conditions where the right answer is to spend the money somewhere else first.
The pattern across all four: AI enablement amplifies a process that already exists. It does not create one. Spending four weeks documenting a workflow and cleaning up where its data lives is not a delay before the real project. It is the highest-return part of the project, and you can do it without a vendor.
There is a fifth version worth naming. If the brief is headcount reduction, be direct about it internally before you hire anyone, because the enablement work looks completely different when the goal is fewer people rather than more output per person, and a partner who finds out later will build you the wrong thing.
How We Would Want You to Evaluate Us
WE•DO does this work, so the fair thing is to answer our own questions in public.
- What we run on ourselves: more than 40 AI agents handle our own research, briefs, reporting, and QA. It is the first thing we screen share, because it is the only credential in this category that cannot be faked. The full roster is published in 40 AI agents every growth team should have.
- Our prices: published. A $3,500 readiness audit, focused engagements at $5,000 to $15,000, ongoing integration at $7,500 a month with a three-month minimum.
- What we refuse to automate: final client-facing approvals, anything involving a judgment about a person, and pricing.
- What you own: the accounts, the prompts, the documentation, and an internal owner who has run the workflow without us.
- Where we are a bad fit: pre-revenue companies, businesses with no repeatable process, and anyone who wants a governance framework rather than a working system.
If a competing firm answers those five better than we do, hire them. That is the point of publishing it.
Questions We Get Asked
How much does an AI consultant cost?
Independent AI consultants typically bill $150 to $400 an hour. Firms scope by project: expect $3,000 to $5,000 for a readiness audit, $5,000 to $15,000 for a focused engagement that puts one workflow live, and $5,000 to $20,000 a month for ongoing programs. Enterprise transformation work runs $200,000 and up. The number that matters more than the rate is the run rate after delivery, which most quotes leave off entirely.
What is the difference between AI enablement and AI consulting?
Consulting produces a plan: assessment, prioritized use cases, a roadmap. Enablement produces a running workflow your team owns, with training and governance around it. Consulting ends with a document. Enablement ends with something that still works after the engagement closes.
How long should an AI enablement engagement take?
For a small or mid-size company, 4 to 8 weeks to get the first workflow live and measured, and about 90 days before the metric you set at kickoff has moved enough to trust. Anyone quoting 12 to 18 months for a company under 100 people is describing an enterprise program.
Do we need clean data before we start?
You need organized data, not perfect data. The practical test: can you export your customer list as a clean CSV in under ten minutes, and do your core tools share data through integrations rather than copy and paste? If the answer is no to both, run a short data project first.
What to Do on Your Next Vendor Call
Open with question two. Ask them to show you an AI workflow their own company depends on, live, before anything else on the agenda. Then ask five and seven. You will know inside fifteen minutes whether the rest of the call is worth having, and you will have saved yourself the proposal review.
And if the answers make you realize you are not ready, that is a good outcome. Document one process, get your data somewhere a tool can reach it, and come back in a month with a much cheaper problem.
Want to run these seven questions on us? Book a working session. We will screen share what we run internally, tell you which of your jobs we would take first, and say so plainly if the answer is that you should not hire anyone yet.
