Owners and operators of small businesses
Your team is already using AI. You just are not managing it.
Nobody asked permission. Somebody on your team pasted a customer email into a free chatbot last week to get the wording right, somebody else used it to draft a quote, and a third person is running invoices through it on a personal account. That has a cost — hours nobody tracks, and customer or financial information sitting in a service you have never read the terms of. The fix is not a ban, which does not work. The fix is giving people AI-boosted tools that solve the problems they actually have, on the devices and systems they already use, with someone accountable for the output.
Questions you already have
These are answerable. Most of them in five minutes.
The assessment is built around exactly these. Your report answers them with your own answers and your own website in front of it.
- What is my team already doing with AI that I do not know about?
- Is customer or financial data leaking into free chatbots right now?
- What is this costing me — in hours, in risk, in duplicate subscriptions?
- Which two or three tasks should I automate first for a real return?
- Do I need a policy, and what does one actually say?
- How do I tell a useful AI tool from a repackaged chatbot with a monthly fee?
Before you start
What stealth AI is costing you
Two numbers and a guess at the exposure, from the size and type of your business. It is an estimate with its assumptions printed on the label — the assessment replaces it with something specific to you.
Include part-time staff and regular contractors.
Sets the typical adoption and wage we start from.
Fully loaded — wages plus taxes and benefits. Leave it blank to use a figure typical for your industry.
The estimate
- Unmanaged AI use
- 10.5 hours a week
- That time, annualized
- $31,395 a year
- People using AI at work
- 7 of your team
About 2 people are likely pasting customer, employee, or financial details into consumer chatbots nobody has approved.
Assumes about 55% of a professional services / consulting team uses consumer AI tools in a given week, roughly 1.5 hours each of unmanaged use, 46 working weeks a year, a fully-loaded rate of $65/hour, and that about 35% of those people put customer, employee, or financial details into a tool nobody approved.
This is an estimate from public patterns of AI use, not a measurement of your business. The assessment replaces it with a number built from your own answers — and tells you what to do about it.
The answer is not a ban — bans move the usage somewhere you cannot see it. The answer is giving people AI-boosted tools that solve a real problem, on the systems they already use, with someone accountable for what goes out.
How we look at it
Which lens bites hardest here
Fletching Vane brings the same lenses to every AI decision. Each one is named, and each name comes with what it means. Here is what they ask in your situation.
- Productnomics Run the roadmap as a portfolio of investments, not a list of requests.
- Tool spend you approve and the hours your team already spends on unmanaged AI are the same budget. The question is what that money is buying — new business, kept customers, or protection — and whether anyone chose the mix.
- Aim. Release. Impact. Tie every release to one measurable outcome, then reinvest on the evidence.
- Give one team one AI-boosted tool for one recurring job, measure the hours and the errors for a month, and decide. That loop, repeated, is the whole adoption strategy.
- Human Operating Core Keep the traits AI cannot replace — integrity, initiative, ingenuity — at the center of how the organization runs.
- The employees already using AI on their own are showing initiative. The fix is not a ban. It is sanctioned tools, on the systems they already use, with a named owner for the output.
- FIIT The four stages an organization moves through to run on decisive data instead of directional data: Fluency, Initiation, Impact, Transformation.
- For a small team, Impact is the whole game: one job, one tool, one month, one measured result. Fluency and Initiation can be a single afternoon.
The work this usually needs
The parts of the job this runs into
Product and business management is specific work. These are the pieces that tend to come due here, and each one has a question you can put to anyone you are thinking of hiring.
- Running a roadmap as a portfolio Deciding, once a year and on purpose, how much of the team goes to new bets, to keeping customers, and to not breaking — then scoring every request against the same inputs.
- Pricing and packaging a product Turning features into something a customer can buy and a finance team can forecast — including what happens when AI capabilities have a different cost shape than the rest of the product.
- Owning a P&L and getting back to profitable Being the person whose budget, headcount, and roadmap have to add up — and making the cuts and the bets that follow from that.
- Repositioning a mature product Changing what a product is understood to be — in the market and inside the company — without breaking the customers who bought the old thing.
- Building the go-to-market data loop Wiring CRM, marketing automation, product analytics, and the website into one loop, so pipeline runs on data instead of on the founder.
- Hiring, developing, and restructuring a team Deciding who to hire first, what a product person actually does here, and how to keep a team shipping while the org around it changes.
- Governing with a board, a budget, and a regulator in the room Making decisions that have to be defensible to people who were not in the meeting — trustees, auditors, a cabinet — and building the reporting that lets them trust the answer.
- Rolling AI out to a real workforce Choosing the tools, writing the governance, redesigning the workflow, and handling the people side — so adoption shows up in the numbers, not just in the demo.
- Making an organization run on data Taking a team from directional reports to decisions made on evidence — the instrumentation, the reporting, and the habit of asking what an outcome would prove before building.
What you get
Your report will include
- An estimate of the hours and dollars your unmanaged AI use is consuming now
- Your exposure: who is likely putting customer or financial data where, and what to do this week
- The two or three workflows in your business worth automating first, and why those — each written as Aim, Release, Impact
- A one-page AI policy outline your team will actually follow
- The questions to ask any AI vendor or consultant before you sign anything
- A close that names the work your situation is asking for, and who has done it
The terms, such as they are
- Free, and it stays free — there is no paid tier behind this.
- We read the website you give us, and nothing else.
- Your answers write your report and tell Matt a real person showed up. Nothing is sold or syndicated.
- No newsletter, no drip sequence, no call on the calendar unless you ask for one.