AI Costs, Explained: What Mid-Market Firms Should Budget For

Why AI costs are hard to pin down

Ask about AI costs and most mid-market firms want one number. 10,000 euros? 100,000? The honest answer: it depends. Not because we're ducking the question. The range is just enormous, from a basic customer service chatbot to end-to-end supply chain automation.

That said, reliable benchmarks exist. And that's what decision-makers need to invest with confidence.

The four cost blocks of AI implementation

Every AI project splits into four cost blocks. Know them, and you'll avoid nasty surprises.

1. Consulting and scoping

Before anyone writes a line of code, you need clarity. What problem should AI solve? What data have you got? Which processes suit automation? This analysis phase runs two to four weeks and costs 5,000 to 15,000 euros. Sounds steep for something with no visible output. But it decides whether the remaining 80 percent of your budget gets invested wisely, or burnt.

Plenty of firms skip this step. They want quick wins. Understandable, but projects regularly head the wrong way and end up costing far more than they should.

2. Data preparation

The most underestimated block by a mile. AI needs data, and in mid-market firms, data is rarely clean, structured or complete. CRM entries have gaps. Spreadsheets use different formats. Historical records live in PDFs. Getting this data ready eats 30 to 50 percent of the total budget on most projects. For a typical mid-market build, that's 10,000 to 40,000 euros.

Real example: a machinery maker wanted AI to optimise maintenance planning. But machine data sat across three different systems, partly handwritten. Merging and cleaning it took six weeks on its own. Twice as long as the AI development itself.

3. Development and integration

The actual technical build: model selection, training or fine-tuning, system integration, API work. Depending on complexity, AI development costs run from 15,000 euros for a standard tool with an API connection to 80,000 euros or more for a custom solution.

Things get expensive when legacy systems need connecting. ERP platforms from the 2000s rarely offer modern APIs. Adapters and middleware can add up to a five-figure sum before you know it.

4. Running costs

AI isn't a project with a finish line. Cloud compute, API fees, model updates, monitoring: reckon on 500 to 5,000 euros a month, depending on usage and infrastructure.

Training gets underestimated too. If your sales team is going to use a new AI tool, they need workshops, documentation and a transition period. No licence fees, but plenty of time.

Typical project sizes for mid-market firms

Entry project (15,000 to 30,000 euros): one clearly defined use case built on existing AI tools. Running costs: 500 to 1,500 euros a month.

Mid-size project (30,000 to 80,000 euros): multiple processes supported by AI, with custom work and system integration. Running costs: 1,500 to 3,000 euros a month.

Transformation project (80,000 to 200,000 euros): AI becomes a strategic edge. Running costs: 3,000 to 5,000 euros a month.

Where firms get AI costs wrong

Mistake 1: only budgeting for technology. The AI tool might be 200 euros a month. Adapting it to your processes, training staff and wiring up data sources costs many times that.

Mistake 2: no budget for iteration. The first AI model rarely lands on target. Every project needs improvement cycles.

Mistake 3: expecting ROI too soon. AI investments typically pay back in 6 to 18 months.

How we cost AI projects

Our approach to AI cost planning for mid-market firms: we always start with a limited pilot, 15,000 to 25,000 euros, with measurable results in six to eight weeks.

The pilot has a second benefit. It shows everyone in the business what AI can actually do. That builds buy-in and makes budget approval for follow-on projects far easier.

AI costs for businesses are predictable. As long as you plan honestly.