What AI Integration Actually Costs a Small Business
AI has two invoices: the one to build it, and the one that arrives every month after. Most budgets only plan for the first.
AI pricing confuses buyers because two very different numbers wear the same name. There is the build - a bounded project with a quote - and the run: API usage, monitoring and upkeep, a bill that arrives every month for the life of the system. Most disappointed AI budgets planned only for the first. Here are both, in 2026 figures, for the three shapes AI projects actually take in small and mid-sized companies.
The three price tiers
- An assistant on your own documents - a chatbot grounded in your files and policies for staff or customers: €5,000 to €20,000 to build, live in weeks. The entry point with the fastest payback.
- An AI step inside a workflow - invoices read and booked, leads qualified and routed, documents classified: €10,000 to €40,000 depending on the systems it must talk to. The AI is often the easy half; the integration is the work.
- A custom agent or AI product - multi-step reasoning, actions taken in your systems, your customers facing it: €40,000 to €150,000 and up, with evaluation and guardrails a structural part of the budget, not a line item.
The running costs nobody quotes
- Model usage. API calls are metered, and for most SMB workloads land between €50 and €500 a month - real money, but rarely the problem. A pilot month on genuine volume makes the number predictable before you commit.
- Evaluation and monitoring. A system that writes to customers or your books needs its outputs checked continuously, not admired at launch. Budget the dashboard and the review hour, every month.
- Data cleanup. In many AI projects, preparing the data is half the work - duplicates, missing fields and contradicting records surface the moment a model starts reading them.
- Model churn. Providers retire and replace models on their own calendar; each swap needs a re-test of your prompts and thresholds. An afternoon per quarter when planned, an outage when not.
Keeping the bill honest
Start with one measured bottleneck: the inbox that eats two hours a day, the quotes that take a week. Automate that, measure the before and after, and let the result argue for the next one. It is how we scope every AI integration, and it is the difference between an AI budget and an AI bet: the first one compounds, the second one gets quietly cancelled in year two.
- 3 tiers: assistant, workflow step, custom agent - know which you are buying
- 50% of many AI projects is data preparation nobody budgeted
- €50-500 per month of model usage for most SMB workloads
AI has two invoices: the one to build it, and the one that arrives every month after.
Frequently asked questions
Is a ChatGPT subscription enough for my business?
For individuals drafting text and answering questions, often yes - and it is the right first step. Integration is a different purchase: the AI reads your data, follows your rules and writes into your systems, unattended. The subscription makes one person faster; the integration removes the task. Which one you need depends on whether the bottleneck is a person's speed or a process's existence.
How do I predict token costs before committing?
Run the pilot on real volume: one month of your actual documents, tickets or calls through the planned model, metered. Extrapolating from a demo underestimates - production inputs are longer and messier - and per-request price lists mislead without your volumes. One pilot month turns the scariest line of the budget into its most predictable.
Do we need our own model?
Almost certainly not. Commercial APIs with good prompting and your data retrieved at answer time cover the overwhelming majority of business cases. Fine-tuning pays off only in narrow, high-volume domains, and self-hosting is a cost centre with rare justifications. Spend the difference on data quality and evaluation - the returns live there.
More on this topic: Artificial Intelligence.
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