ARTIFICIAL intelligence could soon transform how boiler checks and housing repairs are carried out by a Bradford housing association.

Social landlord Incommunities is to trial the use of AI in order to reduce costs and improve efficiency as part of a two year project developed with the University of Bradford.

It will use machine learning to predict things such as boiler checks, general maintenance, and housing repairs, and could also be used to help tenants who might fall into debt.

The project, known as a Knowledge Transfer Partnership, could lead to reductions in people's debt by targeting support to tenants, fewer missed appointments for servicing and the proactive replacement of components prior to a breakdown.

The project has funding of £179,165 for two years from UK Research and Innovation.

Jason Baines, director of ICT and business intelligence at Incommunities, said: “We are committed to ensuring customers are at the heart of our business and that the services we deliver reflect their needs. Using artificial intelligence and machine learning can help us predict and prioritise our services more effectively, reduce costs, and improve efficiencies across the business.”

One example is the number of no-access compliance safety check visits, where tenants are not at home when gas engineers call. Machine learning will use data to reduce the number of no-access visits, improving customer service, safety and making efficiency savings.

A report into the project states: “This will digitally transform the operations and decision-making processes across the organisation to the benefit of the company and enhance the quality of service for customers. Incommunities believe that this project will bring about real benefits in their day-to-day management and operations, play a crucial role in supporting their customers, and overall reduce operational costs.”

Professor Sankar Sivarajah, head of the school of management at the University and principal investigator on the project, said: “One of the fundamental aims of this project is to embed an ethical data-driven business culture by adopting an AI-based innovation strategy for Incommunities.

“Incommunities will address business challenges leading to significant productivity gains by adopting an ethical and responsible data-driven AI strategy for effective operational decision-making across the organisation.

“Our project team, which includes Dr Takao Maruyama and Professor Zahir Irani, with the support of a Knowledge Transfer Partnership associate, will help build internal capacity and capability for Incommunities in embedding digital culture transformation and technical expertise in optimisation models, and predictive and prescriptive analytics.”

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