CAG-2
- Mo Alomari, Chief AI Officer

What 20 housing providers told us about AI

And the gap no one is closing, yet.

In this article - we question how important AI is to the social housing sector, what are the opportunities and challenges are, and what are the important questions each organisation needs to be able to answer.

Over the past six months, my colleagues and I have sat down with more than twenty housing providers - IT directors, heads of asset management, compliance leads, operations directors - for structured conversations about artificial intelligence, in addition to the countless meetings our Customer Success and Account Management teams have had. Not demos, not sales meetings: open conversations about how they are really using AI, what they want from it, and what is stopping them.

 
What they told us was remarkably consistent. And it describes a sector in a strange moment - one the national research confirms. By recent sector studies, more than nine in ten housing providers have experimented with generative AI, yet only a handful have embedded it into how the organisation actually works. NHF-partnered research found 44% of providers have no AI policy at all. Experimentation everywhere; adoption almost nowhere. 
 
Our conversations explain why - and what the few providers closing that gap are doing differently.
Mohammad Shape
Mohammad Alomari - Chief AI Officer

What we heard: the work, not the technology

 Ask housing professionals where AI should help and nobody talks about chatbots in the abstract. They talk about specific, grinding work.
 
Repairs came up in every single conversation - backlogs, rising costs, jobs lost in the system, poor information reaching contractors. As one director summarised: "If you conquer rents and repairs, you've conquered 80% of the complexity."
 
Reporting was a close second. One participant described their weekly ritual: "I spend a lot of my time pulling something off the system, putting it into Excel, manipulating it." Others described waiting weeks for reports that answered questions a director had needed that day. The wish was always the same - ask the system a question in plain English, get an answer in the moment.
 
And compliance administration: certificates arriving by email, each opened, read, interpreted, filed and actioned by hand, across thousands of properties. One IT lead put the ambition perfectly: "It would be so nice if all we had to do was leave them in a folder and the certificates just uploaded themselves into the right place."
 
Notice what connects these. Nobody asked for artificial intelligence. Everyone has asked for work to do itself, with a person approving rather than performing it. Their feedback echoes Aareon’s approach as we’ve implemented it internally, that "AI is there to support people, not replace them". 

Why it stalls

When we’ve talked to housing providers about what’s stopping their AI adoption, the answers were never about technology either.

They were about trust and governance. One IT director described a board excited about AI while the data protection lead was - rightly - asking questions nobody could answer. Another had restricted public AI tools not from resistance but because nobody could say where the data went. Several were drafting their first AI policies; others had formed AI councils.

These are not signs of a sector resisting change. They are signs of a sector taking its responsibilities seriously. Housing providers manage public assets and serve people in vulnerable circumstances; the tolerance for poorly governed technology is rightly low. The mistake is concluding that caution means waiting. The providers moving fastest in our conversations had understood the opposite: governance is not the brake on AI adoption. It is the engine of it.

How ‘Systems of Record’ and ‘Human in the Loop’ will define the approach

Underneath both lists - the work people want done, and the fears that stall it - sits the same structural issue.
 
Housing providers have spent decades investing in software systems of record. They capture tenancies, repairs, payments, complaints and inspections, and they are essential. But their design assumption is to record what has happened.
 
A system of record tells you when a tenant is in arrears. A system of action identifies tenants likely to enter arrears, and prompts intervention early. A system of record confirms which inspections were completed. A system of action monitors throughput against regulatory deadlines and flags the gap while there is still time to close it.
 
Crucially - and this answers the trust question directly - in every case a human decides. A terminology referred to as ‘Human in the Loop’. The system surfaces evidence, reasoning and confidence; the professional exercises their judgement. That is not a limitation of the approach. It is the approach.

 What the few do differently

The providers in our research who had moved beyond experiments shared a pattern. They put boundaries before capabilities: AI operates within explicit scope and escalates what it is not authorised to handle - in a sector where a wrong answer about gas safety has real consequences, knowing when not to act is a design feature. They make outputs traceable: staff trust what they can interrogate, and the first question of any AI output is "why?". They keep accountability human, with clear sign-off points and audit trails. And they start small and prove it - one bounded use case, measured honestly. As one operations director told us: deliver quick wins along the way and "the business believes you."

 

 A leadership question

Our discussions with housing providers have left me convinced the sector is not short of data, ideas or committed professionals. It is short of an operating model that connects them - and that model is built through choices about accountability, boundaries and trust that only leadership can make.

The adoption gap will not be closed by another pilot. It will be closed by providers who treat governance as the foundation rather than the obstacle, and who ask of every AI initiative not "what can it do?" but "what work are we redesigning, who is accountable, and how do we govern it?" The organisations answering those questions deliberately will intervene earlier, act more equitably - and be able to show residents, regulators and boards exactly how.

That is what beyond the hype actually looks like.

 

 

 

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