Every SMB leader asks the same fair question: how much does AI cost? The wrong answer is a single number. The right answer depends on what you automate, the state of your data and the level of integration required. This guide gives 2026 ranges by project type, then the costs most quotes forget, and finally the method to check whether the spend pays off.

The 4 main project types and their 2026 ranges

There are four families of work, from the shortest to the most committing. The ranges below reflect the market of serious providers: neither the cheapest freelancers nor the large firms at 1,500 euros a day. They exclude recurring software subscriptions.

  • AI diagnostic / scoping: 0 to 5,000 euros. A process audit, identification of profitable use cases and a costed roadmap. Often free or heavily reduced if it leads to a project, sometimes funded by Bpifrance.
  • Process automation: 5,000 to 25,000 euros for a first build (follow-ups, data entry, quote handling, tool sync). Cost depends on the number of steps and integrations.
  • Chatbot / AI agent: 8,000 to 40,000 euros. A customer-service agent or internal assistant connected to your data (RAG) costs more than a simple scripted bot. Expect the top of the range as soon as it acts (creates a ticket, edits an order).
  • Custom development: 25,000 to 120,000 euros and up. A specific business solution integrated into your IT system, with its own interface and rules. Price rises with criticality and volume.

A useful rule of thumb: a first profitable automation project for an SMB usually lands between 8,000 and 20,000 euros in the first year, subscriptions included. Below 5,000 euros you are buying a test or a very targeted quick win, not a structural project.

What really drives the price

For seemingly equal scope, two quotes can vary threefold. Four factors explain most of the gap, and none of them is the algorithm itself.

  • The state of your data: clean, accessible data halves the cost. Scattered, messy or out-of-reach data (PDFs, paper, closed tools) inflates the integration bill.
  • The number of integrations: every connection to an existing tool (CRM, ERP, messaging, accounting) adds development and testing.
  • The level of autonomy: an assistant that suggests costs less than an agent that acts unsupervised, because the latter needs guardrails, logging and a fallback plan.
  • Criticality: if an error touches a customer or invoicing, you need more testing, human validation and robustness, hence more budget.

The price of an AI project is rarely set by the model. It is set by the state of your data and the number of things the AI has to plug into.

The hidden costs quotes forget

The classic trap is to look at the build cost and ignore the cost of ownership. Over three years, integration and maintenance often weigh as much as the initial build. Plan for them from the first euro.

  • Integration with the existing IT system: connecting, mapping fields, handling edge cases. Frequently 30 to 50 percent of the first-year budget.
  • Recurring usage cost: model calls, infrastructure, licences. Variable with volume, sometimes underestimated by a factor of three.
  • Maintenance and evolution: an AI project is not delivered once and for all. Budget 15 to 25 percent of the initial cost per year for fixes, updates and adjustments.
  • Human supervision: especially in the first six months, someone must check the outputs. It is a real cost even if it appears on no invoice.
  • Change management: training, documentation, support. A tool nobody uses has an ROI of zero.

How to calculate your return before signing

ROI is not a slogan, it is a subtraction. Start from a measured baseline, not an estimate. Time the current process: how long per operation, how many operations per month, what fully loaded hourly cost. Multiply to get the real annual cost. The credible gain is the share of that cost the automation removes or redeploys.

Concrete example: a process that takes 12 hours a week at 35 euros loaded per hour represents about 21,000 euros a year. A 15,000-euro automation that removes 70 percent of it yields roughly 14,700 euros a year, a payback close to 12 months. That ratio, not the sticker price, tells you whether the project is worth it.

Never ask how much AI costs. Ask in how many months it pays for itself. A payback under 12 months is good, under 6 is excellent.

The most common budget mistakes

  • Budgeting the build but not the three years: ownership often costs as much as construction.
  • Picking the cheapest quote: an underbudgeted project stalls at 80 percent, right before it produces value.
  • Trying to automate everything at once: too wide a scope explodes cost and risk. Start with one process.
  • Forgetting the usage cost: an agent that is cheap to build can be expensive to run at high volume.
  • Not measuring the baseline: with no zero point, you can never prove the gain or decide on the next move.

In short

In 2026, a first profitable AI project for an SMB usually sits between 8,000 and 25,000 euros in the first year, with a cost of ownership to plan over three years. Price depends more on your data and integrations than on the model. Before you sign, demand a range per use case, a costed baseline and an estimated payback. Our approach is simple: we challenge the project, verify the return holds, then we build.