The verdict in three sentences
The genuinely profitable AI use cases in SMEs fall into three families: document search (RAG), data extraction and classification/routing. 2026 budgets run from 4,000 to 18,000 EUR per use case, with LLM API costs of 0.30 to 3 EUR per 1,000 requests by model. The trap is organisational, not technical: without data governance and ROI measurement, the project stays a demo that never reaches production.
Profitable use cases and their budgets
Prioritise use cases with high manual volume and low variability. An assistant that answers from your internal documents (RAG) is the most common entry point.
| Use case | 2026 budget (EUR) | Typical gain |
|---|---|---|
| Document assistant (RAG) | 8,000 - 18,000 | -50 % search time |
| Document data extraction | 6,000 - 12,000 | -70 % manual entry |
| Classification / routing | 4,000 - 9,000 | Automatic request triage |
| Assisted drafting (proposals, emails) | 5,000 - 11,000 | 2x productivity |
| Meeting summarisation | 3,000 - 7,000 | 4-8 h/week saved |
LLM API and infrastructure costs
Variable cost depends on the chosen model and token volume. An economy model is enough for classification; an advanced model is justified for complex reasoning.
| Item | 2026 order of magnitude | Note |
|---|---|---|
| Economy model (1,000 requests) | 0.30 - 0.80 EUR | Classification, simple extraction |
| Advanced model (1,000 requests) | 1.50 - 3 EUR | Reasoning, long summaries |
| Vector database / month | 20 - 120 EUR | By document volume |
| Hosting / orchestration / month | 30 - 150 EUR | APIs, queues |
| Quality supervision / month | 300 - 1,200 EUR | Human review, evaluation |
Mini case study
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Thomas, head of a 30-person engineering firm in Nantes, deploys a RAG assistant over 12,000 technical documents. Project: 14,000 EUR to build, plus 180 EUR/month infra and 400 EUR/month supervision. His engineers spent 6 h/week searching references (loaded cost 45 EUR/h); the assistant removes 3.5 h, i.e. 157 EUR/week per engineer. Across 10 engineers the gain exceeds 6,000 EUR/month: ROI in under 3 months despite recurring costs.
FAQ
Which use case should we start with? The one combining high manual volume, stable rules and available data. Data extraction and document RAG deliver the fastest ROI, often under 4 months.
Does our data go to the LLM vendor? Not necessarily: you can use enterprise offers without training reuse, or even self-hosted models. Data governance is decided during scoping.
Is an economy model enough? For classification and simple extraction, yes, at 0.30-0.80 EUR/1,000 requests. The advanced model is only justified for reasoning or long summaries.
How do we avoid hallucinations? With RAG (answers grounded in your documents), guardrails, and human review on sensitive cases. Budget 300 to 1,200 EUR/month for supervision at launch.
What is the real budget trap? Underestimating recurring costs: APIs, vector database and supervision. Plan 500 to 1,500 EUR/month depending on volume for a production use case.
Let's scope your project. Tell us the target use case (RAG, extraction, classification), document volume and budget, and we'll price a measurable pilot. Detailed quote within 48 h. WhatsApp +221 77 596 93 33.
Mohamed Bah
Fondateur, Kolonell
Passionate about digital and entrepreneurship in Africa, Mohamed has been helping Sénégalese businesses with their digital transformation since 2020. Founder of Kolonell, he believes every SME deserves a professional and accessible online présence.
