Executive summary:
From experimentation to organisational impact
Artificial intelligence is becoming an increasingly familiar part of day-to-day work across social housing. Organisations are exploring how it can improve services, increase efficiency and generate better insight. But while AI activity is widespread among respondents to this research, many organisations are still at an early stage in turning experimentation into consistent, measurable impact.
To understand how AI is being adopted in practice, Housemark surveyed 66 professionals working across housing associations, local authorities and ALMOs. The research explored how AI is currently being used, where organisations are seeing benefits and what is preventing them from scaling adoption further.
The findings provide a snapshot of AI adoption across the organisations represented in the research, highlighting emerging patterns, experiences and priorities.
The survey reveals widespread activity but uneven maturity. Twenty-six respondents, 39%, described their organisation’s adoption as individual experimentation, while 19, 29%, reported team-level adoption and 17, 26%, reported coordinated organisational initiatives. Only three respondents, 5%, said AI was a strategic priority reflected in organisation-wide adoption. One organisation was not currently using AI.
"Access to technology alone will not deliver transformation. Housing providers need to combine practical use cases with stronger data, skills, governance, measurement and clear business objectives."
How would you describe your organisation’s AI adoption?
What the data tells us
Access does not automatically lead to adoption. Thirty-nine respondents, 59%, said all or most staff have access to AI tools provided by their organisation, but only nine, 14%, reported that more than half of staff use AI at least once a week. Many described usage as informal, inconsistent or dependent on individual teams.
Nevertheless, respondents reported practical applications spanning content generation, reporting, data analysis, process automation, predictive modelling, customer service and decision support. Examples included damp and mould analytics, contact centre call summaries, complaints analysis, tenancy sustainability and board reporting.
AI is also changing how analysts, insight teams and technical practitioners work. Respondents described using it to support SQL and DAX development, Power BI reporting, dashboard creation, coding, scripting and workflow automation. For some practitioners, AI is becoming an everyday tool for developing processes rather than simply generating content.
Microsoft’s AI ecosystem, including Copilot and Azure AI, was named as the main source of AI capability by 54 respondents, 82%. Qualitative responses described Copilot being used for drafting, summarisation, reporting, coding, research, meeting support and data analysis.
Access vs adoption
All or most staff have access to AI tools
More than half of staff use AI once a week
Does your organisation have an AI strategy or plan?
Yes – formal strategy
Planning to develop one
Currently developing one
Substantial barriers remain. Only seven respondents, 11%, had a formal AI strategy, although 27 were developing one and 15 were planning one. Skills were selected as a barrier by 53%, followed by legacy systems at 48% and data quality and budget constraints, both at 39%. Improving data quality and upskilling staff were the two most frequently selected priorities for the next 12 months, each chosen by 59%.
The research also exposes a gap between reported benefits and proven impact. Sixty-five per cent agreed or strongly agreed that AI had improved productivity and 62% that it was delivering measurable value. However, just 21% agreed or strongly agreed that their organisation could demonstrate return on investment. Seventy per cent were not measuring AI’s impact and only 5% were doing so consistently.
The conclusion is clear: access to technology alone will not deliver transformation. Housing providers need to combine practical use cases with stronger data, skills, governance, measurement and clear business objectives. The challenge now is turning growing experimentation into measurable organisational impact.