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From data gaps to decisions - Ai and the future of housing intelligence

Housing policy has a data problem. AI may finally solve it.
This session explores how artificial intelligence is transforming housing analytics, helping uncover hidden trends, policy blind spots, and market risks in real time.

Olivia Nielsen

Facilitator

date May 19, 2026 | 13:30 - 14:30 (passed)
place
Urban Library - room A
organization
Miyamoto International
country
United States of America
language
English
Reference: 
UL-A 03

Summary

Housing policy is only as good as the data behind it, but today’s housing data is slow, siloed, and hard to compare. This event looks at how AI can simplify, speed up, and standardize housing data across countries, helping users identify trends, risks, and policy blind spots in real time. Featuring insights from the Global Housing Database, the discussion highlights what’s now possible when housing data meets machine intelligence.

Partners

Organization
Country
Miyamoto International
United States of America

Session panelists

Panelist
Role
Organization
Country
Ms. Kecia Rust
Executive Director
Center for Affordable Housing Finance in Africa
Ms. Dao Harrison
Senior Housing Specialist
The World Bank