Technology
What Could Agentic AI Mean for Tenant Care in Social Housing?
Kay Aston, director of housing solutions at NEC Housing, explores how AI could help the sector deliver more responsive, personalised services for residents.
Kay Aston
FRAUD detection systems used in modern banking have become remarkably good at spotting activity that most humans would miss.
These systems use artificial intelligence( AI) to flag single unusual transactions for additional checks, or identify patterns in thousands of electronic transfers that a human might miss but could indicate fraudulent behaviour by a bad actor.
The housing sector is also increasingly using AI to automate staff workloads and identify properties that may be at risk of issues such as damp and mould, based on historical data like maintenance history and resident complaints.
But the next generation of Agentic AI could be far more transformative as it becomes more widely available in the housing sector.
What is Agentic AI?
Agentic AI can address many of the limitations of traditional AI and take the technology to the next level in housing.
If a landlord wants to reduce rental arrears, traditional AI could calculate the number of missed payments in a 12-month period, identify households that have fallen into arrears, or even indicate what times of the year put pressure on rental income.
This is useful information, but it generally only helps to identify households that are already struggling.
Agentic AI does far more than follow a set of instructions. Given a challenge or end goal, it can analyse huge amounts of data, reason, plan, and deliver a coordinated solution. In this scenario, it could instantly collate rent account data, information on benefits entitlement, historical tenancy records and changes in payment behaviour. This information would be analysed in seconds and a proactive plan produced to reduce rent arrears across the organisation, including a list of elderly or vulnerable residents to prioritise for early outreach to help keep them in their homes, where possible.
The AI-agent could then draft a series of personalised communications to residents, using branding and messaging directly from the housing provider’ s guidelines, and book follow-up visits for housing officers.
Agentic AI will continue to mature over the next three to five years, and there are three strategies housing providers can start putting in place now to fully benefit from this evolution.
1. Prepare your data for Agentic AI
Agentic AI can analyse structured datasets, like property records or maintenance logs. It also has no problem analysing this alongside unstructured information, which could include meeting notes, observations from housing officers following a visit and resident feedback forms. Giving AI agents access to a broader range of information can reduce the risk of bias and uncover subtle insights that analysing structured data alone might miss.
Data should be integrated, accurate and from a trusted source to take full advantage of Agentic AI for semi-autonomous and autonomous decision-making. The technology can then link all relevant details in real time to anticipate issues, prioritise interventions and free staff to focus on delivering safe and comfortable homes for residents.
2. Develop the workforce to use next-gen AI effectively
Preparing housing officers and staff for Agentic AI is as important as preparing data. Upskilling staff early helps them recognise where AI agents can add value and which use cases will have the greatest impact on residents and the organisation.
With the right training, staff also gain confidence and a deeper understanding of how the technology interacts with legacy systems, so they know how to use it effectively to support decision-making. This could include a combination of training programmes, cross-departmental workshops and a team of Agentic AI champions who can build trust in the technology and create a culture ready to take full advantage of Agentic AI.
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