Using AI to improve social housing for the most vulnerable
Using AI to improve social housing for the most vulnerable
Publish Date: 2026-06-23 05:13:00
Source Domain: www.gatescambridge.org
Two Gates Cambridge Scholars are involved in a local project using AI to better anticipate social housing problems for the most vulnerable.
The interesting bit [about this project], which is unique to this project, is that we’re predicting not just on observation data, but also on data from lived experience.
Ramit Debnath
Cambridge researchers, including Gates Cambridge Scholars Adhib Hussain Syed [2025] and Ramit Debnath [2018], are developing an artificial intelligence tool that could tell UK councils which social housing tenants are most at risk before a potential crisis hits.
The project, called PRISM (Predictive Risk Intelligence for Social housing Maintenance), is a collaboration between the University of Cambridge and two local councils: Cambridge City Council and South Cambridgeshire District Council. It is supported by the Local Government AI Accelerator, a new initiative from ai@cam, the University’s flagship mission on artificial intelligence.
Instead of waiting for a tenant to report a leaking roof or a damp bedroom wall, a computer model would scan data from thousands of properties and flag the ones most likely to deteriorate, and the residents most likely to be harmed if they do.
“At the moment we’re very much waiting for things to break before we act,” said Peter Campbell, Head of Housing at South Cambridgeshire District Council, which manages around 5,500 social housing properties. “Quite often when things break, it’s not only the item itself that gets damaged, but also the damage caused by the break. For example, it’s not just the roof that needs replacing; it’s where the water has gotten in and damaged the rest of the property.”
The two councils together manage thousands of tenancies across an unusually wide geography – the urban density of Cambridge city, and the more suburban and rural…
