How much does AI implementation cost in a small business?
The cost of an AI implementation in a small business includes building the tool and using it afterwards. Ongoing support may be another part of the bill: fixes after an API change, document updates or adjustments to a new way of working. It helps to see these items separately in a quote.
An automation that reads an email and puts data into a spreadsheet has a different scope from one that checks an order in the CRM, retrieves prices and prepares a quote for approval. The label “AI implementation” says little about the amount of work involved.
What you pay for during the build
Someone needs to establish where the tool gets its data, what it should do with it and where the result goes. Then they connect the systems, prepare instructions for the model and test the whole process on examples. Error handling and handing the tool over to its users are part of the work too.
Several things affect the quote:
- Integrations. Connecting another system means checking access, data formats and what happens when something fails. Two CRMs can expose the same information in very different ways.
- The state of your materials. If your offer exists in seven versions of a file called “offer_FINAL_v3_fixed”, someone first needs to identify the current one. Missing spreadsheet fields and unreadable documents need attention too.
- How the result is used. A draft reviewed by an employee needs a different level of checking from a reply sent directly to a customer. In both cases, agree which errors are acceptable and who catches them.
- Handover and maintenance. Establish what the instructions, training and later fixes cover, and what will be billed separately.
I quote a project after learning its scope. I specify external tool costs in the quote or project agreement, so you can check which expenses are included in my fee.
What model usage costs
An automation using an API is billed under the provider’s rules. For text models, an important factor is the number of tokens: the pieces of text processed by the model. Input and generated output can have different rates, and some tools carry additional charges. Current details are in the pricing pages for OpenAI, Anthropic and Gemini API.
Counting emails alone is therefore not enough. A short enquiry and a long thread with attachments can use different amounts of data. If the automation calls a model several times for one task, each call needs to be included.
During a pilot, you can measure the cost of the sample you processed, then estimate spending at the expected volume. Include longer documents, retries after errors and a month with more enquiries. The forecast then has explicit assumptions you can compare with the eventual bill.
Make or n8n, hosting, document storage and additional access to a company system can be separate expenses. I compare the platforms’ billing approaches in Make or n8n.
An example calculation
For this example, suppose a task takes 20 hours a month. After automation, 5 hours remain for review and corrections. We value each recovered hour at 80 zł and assume monthly tool and support costs of 200 zł. All amounts in this example are before VAT and are assumptions used to illustrate the calculation.
| Item | Calculation | Result |
|---|---|---|
| Time recovered | 20 h − 5 h | 15 hours a month |
| Value of that time | 15 h × 80 zł | 1,200 zł a month |
| Value after ongoing costs | 1,200 zł − 200 zł | 1,000 zł a month |
| Simple payback period with an assumed build cost of 6,000 zł | 6,000 zł ÷ 1,000 zł | 6 months |
The calculation depends on those assumptions. If checking the output takes 12 hours rather than 5, payback will be much slower. If the number of cases grows, both the value of recovered time and the running costs will change.
Recovered hours do not necessarily mean a smaller payroll payment. An employee might spend them on overdue quotes or handle more enquiries. Establish what the company will actually do with that time before treating it as cash saved.
What to prepare for a quote
A description of the task, a few examples of inputs and finished outputs, and a list of the tools involved are useful. Add the number of cases per month and identify who will check the automation’s work.
When comparing offers, check the scope of testing, fixes after acceptance, charges for exceeding usage limits and maintenance arrangements. If one quote covers only the build while another includes ongoing support, the totals alone are not enough to compare them.
My first consultation is free and takes about an hour. After discussing your needs and scope, I can prepare a plan and quote. You can send a description of the task to [email protected].