AI Invasion: Will Robots Replace Your Housing Officers?

As we stand on the brink of a technological revolution, one question looms large: Will Artificial Intelligence (AI) replace housing officers in the next five years??

Housing officers are the backbone of the housing sector, juggling multiple responsibilities from property repairs to arrears management. However, their work often involves manual data entry across various applications, making the job more time-consuming and less efficient.?

But with the rapid advancement of #AI, particularly 微软 #Co-pilot, this scenario is set to change dramatically*. Co-pilot’s ability to integrate data from multiple internal and external sources presents a golden opportunity to empower customers and streamline operations.?Here are only a few scenarios:

• Imagine a future where customers interact with an AI chatbot to check their balance or pay rent. They could report repairs using plain language and supporting images, speeding up issue diagnosis and reducing the need for return visits.?
• AI could also revolutionise the mutual exchange process by matching customers looking for similar exchanges within their housing association or across the country instantly. Approval processes for pets, building works, and other permissions could be fully automated, providing instant responses based on tenancy and property information.?
• The process of starting tenancies could be streamlined as AI guides customers and colleagues through the process, allowing customers to upload key information and matching them with available properties at housing associations nationwide.?

Undoubtedly, the potential applications of AI in the housing sector are vast and we are just scratching the surface. With core processes automated and customers empowered to provide updates, one might ask the question, do we need housing officers in the future?

The short answer is a resounding yes. The housing sector supports some of the most vulnerable individuals in our communities, many of whom may not have or want access to technology. These individuals often have complex needs that require face-to-face support from well-informed housing officers.?

Even as the housing sector undergoes significant changes, such as mega mergers, the need for personalised support remains paramount. It’s crucial that our vulnerable customers don’t get lost in the sea of big data, represented as just 0.001% of the current customer base (when you have 200,000+ customers to look after).?

So, what could the Job of a housing officer look like in the future If we estimate that automation could potentially eliminate around 70%+ of the role?

AI itself can also be a powerful tool for housing officers, freeing up time currently used to dash from property to property or completing multiple forms.?

Consider a week planned with the help of AI:?

• Core learning time automatically added to the calendar – relevant to the day job or to improve knowledge in a certain area that will support more customers.?
• Automatically informed of Mutual exchange matches – Enabling focused pre exchange visits with customers.?
• Scheduling of visits for the week – targeting properties in a certain area or by a certain customer type, including time for travel and to complete any follow-up work.?
• Automatically know the next stage in a more complex process – safe in the knowledge that AI has taking into account the latest policy/procedure changes, the customers latest interactions with the housing association and any changes in their circumstances.
• Automated creation of a support plan for customers, according to their needs, that is instantly shared with them, so everyone knows what’s going on before the face to face meeting happens

In conclusion, while AI has the potential to revolutionise the housing sector, the human touch remains indispensable. As the role of housing officers evolves, AI can serve as a powerful tool to enhance efficiency and free up time for more value-added tasks.?

*as always there are T&C’s here, the success of AI in housing management hinges on data – its storage, its currency, and its structure. While AI can work across unstructured data, it performs optimally with structured data.?

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