Where do ai and machine learning occupiers lease office space in Mexico City?

Most cluster in Insurgentes / Condesa-Roma. Rent runs ~580 MXN/sqft ($34 USD) for trophy and prime stock.

What fit-out spec do ai and machine learning occupiers run in Mexico City?

Typically high-end at $2600–3900/sqft.

How much office space per seat should a ai and machine learning occupier plan in Mexico City?

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 Mexico City?

78/100. Use the city profile for full detail.

AI and machine learning occupiers in Mexico City typically cluster in Insurgentes / Condesa-Roma, plan ~150 sqft per seat at high-end fit-out ($2600–3900/sqft), and pay around 580 MXN/sqft ($34 USD) on Class A.

Preferred submarket: Insurgentes / Condesa-Roma.
Typical fit-out spec: High-end ($2600–3900/sqft).
Plan ~150 sqft per seat for headcount sizing.
Class A rent context: 580 MXN/sqft ($34 USD).
Typical lease: 5 years with 6 months rent-free.
Talent depth in Mexico City: 78/100.

AI and machine learning office space in Mexico City

AI and machine learning occupiers in Mexico City typically cluster in Insurgentes / Condesa-Roma, plan ~150 sqft per seat at high-end fit-out">fit-out ($2600–3900/sqft), and pay around 580 MXN/sqft ($34 USD) on Class A.

TL;DR

Preferred submarket: Insurgentes / Condesa-Roma.
Typical fit-out spec: High-end ($2600–3900/sqft).
Plan ~150 sqft per seat for headcount sizing.
Class A rent context: 580 MXN/sqft ($34 USD).
Typical lease: 5 years with 6 months rent-free.
Talent depth in Mexico City: 78/100.

Where they cluster

AI and machine learning occupiers in Mexico City typically anchor in Insurgentes / Condesa-Roma. Tech, creative agencies, advertising, hospitality, boutique professional services.

What they pay

Class A rent in Mexico City runs 580 MXN/sqft ($34 USD) on a 5-year lease with 6 months free. Prime submarkets sit at or modestly above the city index.

Spec and fit-out

Typical ai and machine learning fit-out targets high-end specification at $2600–3900/sqft. Branded reception, full client-facing programming, premium furniture, and specialist AV are standard.

Headcount sizing

Plan around 150 sqft per seat blended (workstation + circulation + amenity). A 100-headcount ai office in Mexico City typically targets 15,000 sqft of leasable area.

Talent angle

Frontier research talent clusters near top-tier ML programs and adjacent compute / GPU supply; loft-style trophy stock is the normal fit. Deep banking, professional services, and engineering talent. Strong feed from UNAM, IPN, ITAM, Tec de Monterrey. Spanish-English bilingual professional base growing rapidly.

Tax and lease context

Headline corporate tax: 30%. Net leases. 5-7 year terms with renewal options. Free rent of 4-9 months and TI of MXN 1,200-2,200/sqm typical. Most trophy leases are USD-pegged for international tenants.

Key facts

city	Mexico City
industry	AI and machine learning
naics	541715, 541511, 518210
preferredSubmarket	Insurgentes / Condesa-Roma
preferredFitoutSpec	High-end
fitoutBand	$2600–3900/sqft
sqftPerSeat	150
classARentLocal	580 MXN/sqft/yr
classARentUsd	$34/sqft/yr
vacancyPct	22.6%
typicalLeaseYears	5
typicalRentFreeMonths	6
talentIndex	78
corporateTaxPct	30%

Frequently asked questions

Where do ai and machine learning occupiers lease office space in Mexico City?: Most cluster in Insurgentes / Condesa-Roma. Rent runs ~580 MXN/sqft ($34 USD) for trophy and prime stock.
What fit-out spec do ai and machine learning occupiers run in Mexico City?: Typically high-end at $2600–3900/sqft.
How much office space per seat should a ai and machine learning occupier plan in Mexico City?: 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 Mexico City?: 78/100. Use the city profile for full detail.

Editorial provenance

Reviewed by Miriam Hollander — Lead market analyst. Last updated 2026-04-15. See our methodology and editorial standards.

Primary sources for this page

CBRE Marketview reports — CBRE
JLL Office Insight — JLL
Cushman & Wakefield Marketbeat — Cushman & Wakefield
Savills World Research — Savills
Colliers Global Office Outlook — Colliers

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