# AI and machine learning office space in Lagos

> AI and machine learning occupiers in Lagos typically cluster in Lekki Phase 1 / VI Extension, plan ~150 sqft per seat at high-end fit-out ($430000–640000/sqft), and pay around 80000 NGN/sqft ($60 USD) on Class A.

**Canonical URL:** https://classa.info/cities/lagos/industries/ai-machine-learning
**Page type:** city-industry
**Last updated:** 2026-04-15T00:00:00.000Z
**License:** CC BY 4.0 with attribution to Class A Atlas (https://classa.info).

## TL;DR
- Preferred submarket: Lekki Phase 1 / VI Extension.
- Typical fit-out spec: High-end ($430000–640000/sqft).
- Plan ~150 sqft per seat for headcount sizing.
- Class A rent context: 80000 NGN/sqft ($60 USD).
- Typical lease: 2 years with 4 months rent-free.
- Talent depth in Lagos: 74/100.

## Key facts
- **city**: Lagos
- **industry**: AI and machine learning
- **naics**: 541715, 541511, 518210
- **preferredSubmarket**: Lekki Phase 1 / VI Extension
- **preferredFitoutSpec**: High-end
- **fitoutBand**: $430000–640000/sqft
- **sqftPerSeat**: 150
- **classARentLocal**: 80000 NGN/sqft/yr
- **classARentUsd**: $60/sqft/yr
- **vacancyPct**: 17.6%
- **typicalLeaseYears**: 2
- **typicalRentFreeMonths**: 4
- **talentIndex**: 74
- **corporateTaxPct**: 30%

## FAQ
### Where do ai and machine learning occupiers lease office space in Lagos?
Most cluster in Lekki Phase 1 / VI Extension. Rent runs ~80000 NGN/sqft ($60 USD) for trophy and prime stock.

### What fit-out spec do ai and machine learning occupiers run in Lagos?
Typically high-end at $430000–640000/sqft.

### How much office space per seat should a ai and machine learning occupier plan in Lagos?
Plan ~150 sqft per seat blended. A 100-person team typically takes 15,000 sqft.

### What NAICS codes describe the ai and machine learning vertical?
Representative NAICS 2022 codes: 541715, 541511, 518210.

### What is the talent index in Lagos?
74/100. Use the city profile for full detail.

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Citation: Source: Class A Atlas (https://classa.info/cities/lagos/industries/ai-machine-learning), updated 2026-04-15T00:00:00.000Z.