The verdict in three sentences
Business AI is never deployed in one go: you first validate feasibility with a POC (USD 15k-30k), then industrialise a production model for USD 30k-80k. For a Dubai firm, productivity gains reach around 20% throughput on the targeted use case, with ROI in 8 to 14 months. Data governance and regional hosting are built in from the POC.
POC then production: the two budgets to plan
Skipping the POC is the leading cause of AI project failure. The POC validates available data, achievable accuracy and real ROI before committing the larger production budget.
| Phase | Cost (USD) | Timeline | Deliverable |
|---|---|---|---|
| Scoping & data audit | 5,000 - 10,000 | 1 - 2 wks | Costed feasibility |
| POC (proof of concept) | 15,000 - 30,000 | 4 - 8 wks | Tested model, measured accuracy |
| Production rollout | 30,000 - 80,000 | 8 - 16 wks | Model integrated into systems |
| MLOps & monitoring | 600 - 1,800 /mo | ongoing | Monitoring, retraining |
Cost per use case and expected gains
Inference cost is often negligible (USD 0.002-0.012/request); the real line items are development and integration. Here are 2026 order-of-magnitude figures per industrial use case.
| Use case | Production cost (USD) | Productivity gain | Estimated ROI |
|---|---|---|---|
| Visual quality control | 45,000 - 80,000 | 25 - 30% | 9 - 12 months |
| Production planning | 40,000 - 65,000 | 15 - 20% | 10 - 14 months |
| Predictive maintenance | 50,000 - 80,000 | 20 - 25% | 10 - 13 months |
| Inventory optimisation | 30,000 - 60,000 | 15 - 22% | 8 - 12 months |
| Anomaly detection | 35,000 - 65,000 | 18 - 25% | 9 - 13 months |
Mini case study
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Omar, GM of a 70-person manufacturing firm in Dubai, lost 4% of output to defects caught too late. A visual AI quality-control POC (USD 22,000) hit 96% accuracy on his parts. Production rollout (USD 65,000, inference USD 0.005/part) cut scrap by 60%, an estimated saving of USD 9,000/month. ROI across POC + production: about 11 months, regional hosting and governance included.
FAQ
Why not go straight to production? Without a POC you commit USD 30k-80k with no guarantee on accuracy or ROI. The POC de-risks the project for USD 15k-30k.
What's the recurring cost of an AI model? MLOps (monitoring, retraining) runs USD 600-1,800/month; inference at USD 0.002-0.012/request stays marginal.
Is my data governance compliant? We host and train in-region with anonymisation and a processing register aligned to local regulations.
How long to ROI? On average 8-14 months by use case; quality control and anomaly detection are fastest.
Do we need a lot of data to start? A POC can launch with a few thousand labelled examples; the scoping audit confirms this before any commitment.
Let's scope your project. Describe the industrial process to optimise and your volumes: we'll scope a costed POC and give you a realistic ROI projection. 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.
