How much does AI implementation cost in 2026? Prices, running costs and pitfalls

What the cost is made of

The bill for AI in a business has two parts. The one-off part is the work: analysing the process, building it, connecting it to your systems, testing on real data and handing it over. The running part is everything that works afterwards and has to be maintained.

Implementation prices

A starting price is the smallest sensible scope: one process, one channel, one source of knowledge. Every further system to connect, every exception in the process and every new data source is extra work, which is why I give the exact, fixed price in writing after a 30-minute call.

What the AI model costs, worked out on price lists

Language models are billed in tokens, pieces of text that are often shorter than a word. You pay separately for the text sent to the model (input) and for its answer (output). Providers quote prices in dollars per million tokens, and a large model can cost twenty times as much as a small one.

Example 1: a chatbot on a website. Say 1,000 conversations a month, each with four customer questions. With every question the model receives the instructions, the matching passages of your knowledge base and the conversation so far, about 3,000 tokens in all, and the answer is about 250 tokens. A month comes to 12 million input tokens and 1 million output tokens:

• small model ($0.10 and $0.50): 12 × $0.10 + 1 × $0.50 = $1.70, about PLN 6.67;
• large model ($2 and $10): 12 × $2 + 1 × $10 = $34, about PLN 133.

Example 2: categorising purchase invoices. 300 invoices a month, each about 1,500 input tokens and 100 output tokens. On the small model: 0.45M × $0.10 + 0.03M × $0.50 = $0.06 a month, about PLN 0.24. Here the model’s cost is negligible; what counts is the build and keeping the flow running without interruptions.

I convert to PLN at the National Bank of Poland’s average rate of 12 October 2026 (1 USD = PLN 3.9211). How VAT applies to foreign providers’ fees depends on where your business is registered: check with your accountant.

An automation tool or your own server

I build flows in n8n, Make, Zapier or my own code. Cloud tools have a subscription: the cheapest paid n8n plan costs €20 a month billed annually, Make starts at $9, and Zapier at $19.99 billed annually (as of 10 October 2026; details in the comparison n8n, Make or Zapier, in Polish).

The Community edition of n8n can run on your own server with no licence fees, as long as it serves the company’s internal needs. You then pay for the server: the smallest VPS at OVHcloud costs PLN 16.32 net a month when paid 12 months in advance (Polish price list). Your own server gives you full control over the data, but someone has to update it and look after the backups. I include that work in support.

Costs that are easy to miss

• Changes at the providers. Models and tools change several times a year: new versions come out, old ones are retired, prices move. A deployment needs a review every now and then.
• Personal data and the GDPR. If personal data passes through the AI, you need a legal basis, information for the people the data is about, and a data processing agreement with the provider. OpenAI states that data sent through the API is not used to train models unless you opt in. Anthropic commits in its commercial terms not to train models on customer data. Google does not use content from the paid Gemini API plan to improve its products; on the free plan it does.
• AI Act duties. From 2 February 2025, businesses that use AI systems must take measures to support the AI literacy of the people who use them (art. 4, as amended by Regulation (EU) 2026/1744). From 2 August 2026, a chatbot must say it is an AI system unless that is obvious (art. 50(1)). A short introduction for the team and a notice in the chat window cost little, but they have to be planned.
• Your team’s time. Someone has to describe the process, give examples and check the results at the start. Usually a few hours, but without them even a good build will miss the actual needs.

How to tell whether it pays off

The simplest sum: the hours the task takes today each month, times the cost of an hour of work, minus the monthly cost of the solution. The difference shows how many months the build takes to pay for itself.

1. 01

   Count the hours

   For a week, note how long the task takes and scale it to a month.

2. 02

   Count the costs

   The build once, plus the model, the tool and support each month.

3. 03

   Compare

   Example: 10 hours a month at PLN 60 is PLN 600. With running costs of PLN 100 a month, PLN 500 is left, so a PLN 2,500 build pays for itself in five months.

4. 04

   Start with one process

   The one that takes the most time and has the fewest exceptions. Add the next ones once the first runs reliably.

Examples and prices are on the page AI automation for businesses, and the difference between a chatbot and an agent is in the guide chatbot or AI agent.

Prepared with the help of AI tools, checked and completed by the author. Numbers and regulations come with sources.