How to use AI in my business: what to automate first and what to leave alone

How to use AI in my business is the question owners bring us. This page shows how we answer it in an AI readiness assessment: write down how your work really runs, cross off the ideas that should stay with a person, and put what is left in the order to build it. It is for owners of a small business who think AI could help but do not yet know where to point it. By the end you can test any idea with three questions, put what survives in a safe order, and follow a week-by-week roadmap on your own.

The assessment comes before any building for a plain reason. The three questions cross off the ideas that would have been built wrong, before anyone pays for them, and the hours a job takes are measured before a tool is chosen. A build that skips the assessment usually automates the wrong job, or the right job on a rule nobody had settled.

An invented example: an owner lists eleven things she would hand to AI. An hour later four are crossed off: two happen a few times a year, three people do one of them three ways, and one would send a customer a wrong answer in writing.

What an AI assessment for a small business is for

An assessment worth your time hands your list back shorter, with a reason beside each removal that you can apply again on your own. In a small business every idea that gets built becomes a job someone has to own. Crossing four ideas off eleven saves four builds and four failures nobody would have noticed, before any money moves. Before you look at any tool, decide that the result you want is a shorter list.

Start with one job written down

The three questions need one real job written down first, in the order it happened, including the steps that exist only because a system does not do what it was bought to do. The workflow automation article on this site shows how, with a piece of paper.

An invented example: a two-chair dental office writes down how a new patient gets booked. The front desk takes the call, types the details into the booking program, types them again into the billing program, and sends a reminder by hand. Four steps, two of them the same typing. Write down the job you did most often last week, tonight, the same way.

How small businesses use AI in 2026

Fewer firms use AI than the headlines suggest. The Census Bureau's Business Trends and Outlook Survey put AI use in any business function at 19.8 percent of US businesses as of May 3, 2026 (Census Bureau, May 26, 2026). The Federal Reserve's Small Business Credit Survey asked firms with 1 to 499 employees a wider question, whether the business or its employees use AI in some way, and 46 percent said yes, mostly for writing and marketing (Federal Reserve Banks, March 3, 2026; 6,525 responses, fielded September 3 to November 14, 2025).

A Census Bureau working paper on the survey's 2026 AI supplement, reference period November 2025 to January 2026, splits use by size (Bonney and others, Census Bureau working paper CES 26-25, April 2026). Firms with 1 to 4 employees were at 18 percent; firms with 250 or more were at 31 percent and expected 40 within six months.

The trade matters as much: as of May 3, 2026, the Information sector was at 39.7 percent and Retail Trade at around 14 percent.

You are almost certainly not behind

With four firms in five not using AI inside their work, there is no settled playbook yet, so ask any confident advice, this page included, what it rests on. Of the firms with no plans, 65 percent said AI is not applicable to the business.

A four-person landscaping company might say that before it counts one customer's address typed three times per job, into the quote, the schedule and the invoice (an invented example). Count that in your own business first.

What it does to the team

Among AI-using firms the working paper found sales and marketing the most common use (52 percent of users), and 85 percent of firms whose workers use generative AI used it for writing and editing.

What it did to the work: 44 percent said it added to tasks their workers already do. Headcount barely moved, with 2.3 percent of AI-using firms reporting an increase and 2.0 percent a decrease.

That is how we build: the person stays, and the system takes the repeated typing, copying and checking off their desk. An invented example: a bakery's system drafts each wholesale order confirmation, and the person at the counter, who knows the regulars, reads it and sends it.

The three questions: is it worth automating at all?

These three questions each take a different kind of idea off a list. Run each idea past them in order, and stop at the first no.

One: it happens often enough that a failure gets noticed within a week

A job that runs several times a week reports its own failure, because someone is waiting for the result. A job that runs four times a year can break in March and be found in June by an annoyed customer. Weekly or more is a yes; quarterly is almost always a no.

Two: the rule can be written down for a new hire

An invented example: three people in an office describe the same decision three ways. Nobody is wrong; the rule was never decided, and software built over the top freezes whichever version its builder heard. Ask the three separately, never in a meeting. Different answers mean deciding the rule comes before any build.

Three: a wrong answer lands where a person sees it first

A wrong figure in a sheet someone checks on Friday costs an hour. A wrong answer sent to a customer in writing costs the customer and then the business. This question removes the most ideas, and better software does not change its answer, because where a mistake lands is a fact about the business.

Try your own numbers. From 12 ideas (an invented example), if 65 percent happen often enough, 70 percent of those have a writable rule and 60 percent of those land where a person sees them first, about 3 are left. It is meant to come out small.

The federal AI Risk Management Framework from the National Institute of Standards and Technology agrees: it lists the responses to a risk as "mitigating, transferring, avoiding, or accepting", so not building is a legitimate result, and it "does not prescribe risk tolerance". Version 1.0, from January 2023, was still current on October 31, 2026 (NIST AI 100-1; NIST, AI RMF page).

What should not be automated

Three kinds of work stay with a person in every assessment we run: any fact a customer relies on, such as a price or a policy, unless the system reads it from the record that governs it; the judgment calls made a few times a year, such as taking on a client; and anything whose failure is silent, such as a reminder that stops sending without an error. A fourth test costs nothing: anything you would be embarrassed to say a machine did.

The first kind gets built most often. A model asked about a price will answer, and the risk is a wrong answer in the right format that nobody checks. The right build is smaller: it fetches the value from the record that governs it and says so when there is no record. It may report what a source says or say it does not know.

In a property business, specifically

We started in real estate. Square footage, a tax figure or a permit reads like data and behaves like liability, because a buyer may rely on it. The build worth doing reads each value from the listing record or the public tax roll and says when the record is silent. Whether to take a listing or advise a price cut stays with the agent. Mark every idea on your list that states a fact to a customer, and ask where that fact is read from.

Who should stay on the job

We build AI to add to what your people do, and a person stays on anything a customer sees. The system drafts the reply, fills in the details and finds the past job that looks like this one; a person reads it and approves it. The step that sends cannot run without that approval, and that is built into the system rather than written in its instructions: it either has no way to send, or it checks an approval it cannot give itself.

Four checks decide who runs a job. Does the result bind the business, such as a price or a promised date? Does it reach a customer? Does it feed another system people act on, such as the books? Could it damage trust if wrong? One yes means a person approves every result; with two or more, the binding part stays with that person alone.

The one exception is a fixed message whose exact words you approved once, with only the name, date and time filled in, such as an appointment reminder. Anything a model writes is approved every time. An invented example: a plumbing office's system drafts each quote follow-up, the office manager reads and sends it, and the price is never written by the system. For every idea that survives, name the person who approves it.

Why ranking by the average outcome gets it wrong

With a short list, the natural move is to estimate what each idea is worth and start at the top. We sort by how contained the worst case is. Most jobs come in close to plan; a few go badly wrong, and an average blends both into a number that describes neither.

An invented example: idea A saves three hours a week, and when it fails someone redoes the work for an afternoon. Idea B saves nine, and when it fails wrong confirmations reach customers for a week. On the average B wins; on the worst day A goes first, because a first build that fails quietly teaches a business to distrust the whole idea. Write each idea's worst day beside it, and sort by that.

The failure rate nobody can give you

We found no 2026 public survey of how often a small business's automation fails. The most quoted project failure figure comes from a report sold by a private research firm whose data has never been opened to inspection. Two researchers at Vrije Universiteit Amsterdam applied its definitions to real project records and found they "result in meaningless figures" (Eveleens and Verhoef, IEEE Software, 2010): a project counted as late or over budget, never early or under. A number whose method nobody can check stays off this page. When anyone quotes you a failure rate or a saving, ask how it was measured.

What the order gets sorted by

First, containment: what happens when it is wrong, and who finds out. Second, whether the rule is settled, because software will not make a management decision. Third, and only third, the size of the saving, because the biggest saving is often the job with the most judgment in it.

Our plan also scores each job from 1 to 5 for impact and for risk, each with its reason, and leaves alone a job worth under two hours a week.

An invented example: a Friday list of open quotes for the owner. Only the owner reads it, so a wrong line costs a minute: risk 2. It saves two hours of digging: impact 3. It goes near the top, checked by the owner for four Fridays before it runs alone.

What the assessment is and how it runs

This page is the whole method, and you can run it without us. If you ask us to run it, the assessment is a one-hour call with you, or with you and your manager, and a written plan after it.

Why this is different from an automation agency

Most people selling automations start from the tool. We start from the person who does the work and the hours they get back, keep a person on anything a customer sees, and tell you in writing what not to build.

The steps, in order

Before the call. Your written answers to the questions below, and the four things listed after them. Bring your manager if someone else runs the admin: you know how the business should run, and they know how it does.

The call. One hour on the last real week, because "walk me through last Tuesday" finds the real jobs. We pitch nothing, name no tools and promise no savings.

The notes. Within two business days, sent back for you to correct.

The scoring. Every step labelled, impact and risk with reasons, and one verdict per job: let a system run it, keep a person on it, or leave it alone.

The plan. Built from the scoring, about three business days after the call, then a short call to walk you through it.

The route you pick. We build and run it, or you build from the plan. Either way it runs in your accounts.

The questions we ask in an assessment

Answer these in writing, about the last real time something happened, before you talk to anyone: the answers are the first half of an assessment.

The business in five minutes

1. What do you sell, to whom, and where? How many people work here, and who does what?
2. What is a customer worth to you on average, and do they come back?
3. How many new enquiries come in during a normal week, and from where?

Last week, walked through

1. Take last Tuesday, from the first message to the last. What happened, and which of it happens every week?
2. Walk one job from the first enquiry to getting paid. Who touches it, how long does each step take, and how often a week does it happen?
3. When an enquiry comes in at 2pm on a Tuesday, what happens? And at 9pm on a Saturday?

The job list

1. Which two of your programs do not talk to each other, and how does information get between them today?
2. How many times does the same piece of information get typed into something, by anyone?
3. For each repeated job: if you stopped doing it tomorrow, what would break, and who would notice?
4. If two of your people hit the same case on the same day, would they handle it the same way?

The numbers

1. Roughly what does an hour cost you for the person doing the most repetitive job, counting wage, taxes and benefits?
2. How many calls do you miss in a week, and what happens to a missed call now?

What you want to build

1. Which single task do you most resent doing?
2. If you had 40 hours a week back across the business, what would you do with them?
3. If this worked, which number would move?

What you would never hand to a machine

1. Where do you not want a system involved at all?
2. What has to be true before anything goes to a customer, and who approves that today?
3. What is sensitive here, such as customer details, prices or staff information?

Before the call, send a week of your calendar, the tracker you run the work from, two real messages you sent customers, and your quote template. A good answer to question 8 sounds like this invented one: "Every new customer is typed in three times: the phone log, the quote and the invoice. About 25 a week."

What you get at the end

Your time is the hour on the call and about another hour later for the notes and the walk-through. The plan, written from what you told us, says what we would build and in what order, how, how long each piece takes, and which system does which job. It names the precautions: what stays with a person, what is checked before anything reaches a customer, and how a failure shows. For every repeated job it gives the scores with reasons, the verdict, current hours and a four-week trial target, plus what we crossed off and why, and our open questions instead of guesses. Hours back are a trial target, never a promise, and every number says how it is known.

Two routes from the plan

If you ask us to build it and run it, the assessment is included in that work, and only then do we talk with each person who does the jobs being built. If you build it yourself, the plan is your map, and this page's method is open to you.

Systems break: a program changes, a rule moves, and a job that ran for months stops without an error. A system needs proper evaluation and regular check-ins after it goes live. We have already made the mistakes a first-time builder makes, and the fixes are in the way we build. That is why a monthly retainer for us to build and manage it is safer and more efficient than finding or training someone to learn those mistakes on your business.

What an assessment does not do

It does not decide for you or see what nobody will say, and it goes stale within months, because your business moves. A found hour has to be spent on purpose, or it is absorbed within a month.

How to run one yourself in one evening

1. Write every idea down without judging it.
2. Ask the rule question to three people, separately.
3. Before writing any benefit, write where a wrong answer would land and who would find out.
4. Cross off every line where the answer is a customer, or nobody.
5. Put the list away for two weeks, then read it again.

Your roadmap, week by week

Nothing here needs us, and nothing costs money until an idea has passed every test. Where no job repeats yet, writing the process down comes first.

1. Week one. Write down one job, answer the questions and run the one-evening test.
2. Weeks two and three. Let the list sit, decide the unsettled rules with the people who do the work, and check whether a program you already pay for does any job on it.
3. Week four. Pick the idea with the smallest worst day and name its approver.
4. Weeks five to eight. Run a four-week trial with a person approving every result, and count the hours before and after. If it reaches a customer, the person stays on it for good; if not, and four weeks needed no corrections, it can run alone.
5. Every few months. Read the list again.

An invented example: a cleaning company keeps seven of eleven ideas and in week four picks the Friday list of the next day's jobs for the crews. By week eight it knows the list saves about two hours a week, measured rather than promised.

Common questions about using AI in a small business

How do I use AI in my business?

Write one job down, list your ideas, cross them off with the three questions, and build the survivor with the smallest worst day.

How can AI help a small business?

Mostly by taking repeated typing, copying and checking off people's desks; see what it does to the team, above.

What is an AI assessment for a small business?

A structured look at how the business runs, to decide which repeated jobs AI takes first and which stay with a person; some firms call this an AI audit.

What can I automate in my business first?

Usually something plain that passes all three questions and fails where you can see it: a confirmation, a reminder, a copy from one system to another.

How do you decide what not to automate?

With the three questions above; any one no is enough.

Can I do an AI assessment myself?

Yes: writing a job down and answering the questions costs nothing. The crossing off is harder alone, because every idea on your list is there for a reason you agree with.

How long does an AI assessment take?

One hour on the call with you, and the plan about three business days later; see how the assessment runs, above.

Do I need to know anything about AI first?

No. The three questions are about the business. Choosing the tools is our job.

Does using AI mean fewer staff?

Rarely; see what it does to the team, above.

How is an AI assessment different from workflow automation?

Workflow automation is the building. An assessment is the deciding, and it comes first.

Next step

The offer is the one-hour assessment: we go through your list with you, then send back a written plan of what we would build first, how, and what we would cross off. Book a Consultation: (914) 875-2424, levan@realtylt.com.

By Levan Tsiklauri.

Sources

• U.S. Census Bureau, Adam Grundy, Cory Breaux and Dhanapati Khatiwoda, "Large Firms With at Least 20 Employees Biggest AI Users", America Counts story, May 26, 2026. Business Trends and Outlook Survey, data from December 14, 2025 to May 3, 2026. Read October 31, 2026.
• Kathryn Bonney, Cory Breaux, Emin Dinlersoz, Lucia Foster, John Haltiwanger and Aditya Pande, "The Microstructure of AI Diffusion: Evidence from Firms, Business Functions, and Worker Tasks", U.S. Census Bureau, Center for Economic Studies working paper CES 26-25, April 2026. The 2026 AI supplement to the Business Trends and Outlook Survey, reference period November 2025 to January 2026; all shares firm-weighted. Read October 31, 2026.
• Federal Reserve Banks, Small Business Credit Survey, 2026 Report on Employer Firms, press release of the Federal Reserve Bank of Cleveland, March 3, 2026. Fielded September 3 to November 14, 2025; 6,525 responses from firms with 1 to 499 employees. Read October 31, 2026.
• National Institute of Standards and Technology, Artificial Intelligence Risk Management Framework (AI RMF 1.0), NIST AI 100-1, January 2023, sections 1.2.2 and MANAGE 1.1 and 1.3; NIST's framework page, read October 31, 2026 (version 1.0 current, a revision in progress).
• J. Laurenz Eveleens and Chris Verhoef, "The Rise and Fall of the Chaos Report Figures", IEEE Software, January/February 2010. Cited for how a failure rate was defined, not for any rate. Read October 31, 2026.
• A search for a 2026 public survey measuring how often small-business automation fails returned none on October 29, 2026.

Sources checked October 31, 2026.

Written with an AI assistant and checked by Levan.