Most mid-sized companies now use AI somewhere. Saying what it saves them is harder.
Someone drafts emails with a chatbot. Someone else has a tool that summarises meetings. A pilot from last spring worked well in the demo and then quietly stopped being used. The licences keep renewing, and nobody can point to an hour or a dollar it has saved.
The gap shows up in survey data too. RSM surveyed 966 mid-sized companies in the US and Canada in early 2025. Of those using generative AI, 70% said they need outside help to get full value from it. The most common barrier, named by 39% of respondents, was a lack of in-house expertise.
This guide explains what a useful AI consultant does for a small or growing business, how to implement AI step by step, and what your team should own when the work is done.
What an AI consultant does for a small business
The job is closer to operations than to technology. A good AI consultant spends the first part of the work understanding how your business runs, and only then decides where AI belongs in it.
From there the work has five parts. The consultant finds where AI pays, builds the system inside the tools you already use, and adds the checks that make the output trustworthy. Then they hand it to your team and measure what it delivers. A consultant who skips the checks or the handover can leave you with another demo.
The test of an AI project is what still runs six months after the consultant leaves.
When a small business needs an AI consultant
You may not need one. If the jobs are simple and your team has a little time, you can start alone. Outside help earns its fee in these situations:
- Your team uses AI tools, and nobody can say what they save. Someone needs to measure before anything else gets bought.
- A pilot worked in a demo and stalled in daily use. Check whether it ever fitted the real workflow.
- The same reports, drafts or checks are rebuilt by hand every week. These are the easiest wins.
- You want AI in customer-facing work. That needs checks you can rely on before anything reaches a customer.
How to implement AI in a business, step by step
1. Map the work
Start with the work itself. Write down the jobs your team repeats, who does them, how long they take and what goes wrong. The best candidates are frequent and rule-based, with a clear way to tell a good result from a bad one.
2. Choose one or two places to start
Resist the urge to automate everything. Pick for value and for how quickly the output can be trusted. Weekly reporting, first drafts of proposals, sorting incoming requests and checking figures before they go out are common first choices.
3. Build and check
Build the system where the work already happens, in your email, documents, spreadsheets or CRM. Then design the checks. Decide what a person always reviews, what the system must never do, and how a wrong answer gets caught before it reaches a customer.
4. Hand over and measure
Train the people who will run it, and write down how it works in plain language. Set a measure before launch, such as hours saved or errors caught, and check it after the first month.
What your team should own when the consultant leaves
This is the part most worth negotiating before you sign. When the engagement ends, four things should belong to you:
- The workflow. A written description of what the system does, step by step.
- The instructions and checks. The prompts, rules and review steps, kept where your team can read and edit them.
- The accounts and data access. Set up in your company's name, with no dependence on the consultant's logins.
- An owner. One named person who is accountable for the system and knows how to change it.
Questions to ask before you hire an AI consultant
- What will still be running six months after you leave? The answer tells you whether they build for handover.
- Whose accounts will the systems run on? Yours is the only good answer.
- How will you check that the output is right? Listen for specific review steps.
- What will you measure, and when? A good answer names a number and a date.
- Can you show us a system you run in your own business? Consultants who use AI daily have already found where it breaks.
How we approach AI implementation
We run our own firm on AI systems we built, covering research, drafting, number checks and project tracking. We bring the same approach to clients, using the steps above. Read more about our AI implementation consulting.
Common questions
How do you implement AI in a business?
Map the jobs your team repeats and choose one or two where AI saves real time. Build the system inside your existing tools and add checks. Then hand it to a named owner and measure the result.
Does a small business need an AI consultant?
Not always. Simple jobs can be automated in-house. A consultant pays back when pilots stall or output has to be reliable enough for customers. It also helps when nobody on the team has time to build.
What does an AI implementation consultant do?
They find where AI is worth using, build working systems, add the checks that make them reliable, and train your team to run them.
Source: RSM US, 2025 middle market AI survey, published 11 June 2025. 966 respondents (762 in the US, 204 in Canada), surveyed February to March 2025. The 70% figure is among respondents using generative AI. RSM sells AI consulting. rsmus.com
