AI ain’t all bad: boosting tenants housing engagement experience

By now, we’re all familiar with artificial intelligence (AI). From social media to social care, the technology seems to be dipping it’s toes in various sectors and has now made its way into the housing world.

Since its introduction, the technology has received a mixed response, with some people believing it to be a government-designed platform that analyses people through their computers and phones. Although, Rosie Watts, customer success manager at Orlo – the UK’s number one social media management platform – has informed NewStart that AI isn’t all bad. With ever-stricter regulations on tenant engagement looming within the housing sector and the demand for affordable properties being through the roof, housing associations have begun to utilise the power of AI to meet expectations.

The big question I hear time and time again from housing associations is: how do we improve tenants’ ability to self-serve through the application of AI? The technology can be daunting, especially if it’s not implemented correctly, whether that be too much too soon, or staff not being trained properly.

For the strategy to work – ultimately, we want tenants to use AI services with an aim to speaking to landlords or letting agencies quicker about issues regarding their homes – everyone within the organisation should understand the reason behind the adoption of AI within the business to reduce the fear factor. It’s important to note that AI should not be seen as a human replacement, but rather as an enhancement to the contact centre.

Filling the gaps on why AI is needed in the housing industry

AI offers the potential to help housing organisations use limited resources more effectively and improve how they deliver services, especially during periods of intense financial pressure.

Currently, as a result of the growing cost-of-living crisis, leading housing charity, Crisis, estimates that 145,000 affordable homes are needed in England. On top of this, as prices climb landlords and local authorities have had their budgets squeezed, meaning they can no longer afford to tend to a vast amount of maintenance issues, leaving residents to live in poor conditions.  

However, AI can help to improve Return on Investment (ROI), as it allows human resources to spend their time on cases that really matter. If we strip the role of a housing association’s first response agent down to what their core responsibilities are, it’s about providing a single source of truth and delivering the expected level of care for the tenant.

If, for example, 80% of inbound enquiries are FAQs around easily accessible resources and the other 20% require a deeper level of understanding and care, then AI could be your secret weapon. Digitally deflecting the majority of inbound enquiries with seamless customer service for tenants allows agents to excel in their roles and step in when a human approach and particular expertise are needed.

Rest assured, adopting a self-service approach is still puts tenants needs at the forefront, with team efficiencies to boot. AI-powered technologies such as Live Chat and Chatbots are easing the burden on agents and helping manage increased inbound demand around common enquiries such as rent payment, maintenance requests or account balances, empowering tenants to self-serve 24/7. The result – queries can be solved quickly, at scale, and agents are freed up to handle more complex interactions coming in via other channels or that require a human touch.

How AI is helping with internal operations

Despite Live Chat and Chatbots being viewed as the most prevalent forms of AI within the housing sector, there are so many other uses to help with internal efficiencies that directly impact the tenant. Housing associations can use AI to turn up large volumes of data very quickly into actionable insight.

For example, emerging trends and reputational issues that would previously take a human eye hours to discover, can be alerted to all stakeholders within seconds, reducing the risk of issues turning into potential crises.

Some examples of this include:

• Predictive maintenance: AI can be used to predict when maintenance or repairs may be required on properties. By analysing data from IoT sensors, such as temperature sensors or humidity sensors, AI can detect anomalies and alert housing associations to issues before they become major problems
• Resource allocation: Housing associations can use AI algorithms to optimise the allocation of resources such as staff, equipment, and supplies. AI can analyse data on the number of maintenance requests, occupancy rates, and other factors to help housing associations make informed decisions on how to allocate resources
• Fraud detection: the technology can help to detect fraudulent activities, such as false insurance claims or fraudulent rental applications. AI algorithms can analyse data and flag any suspicious behaviour, helping housing associations prevent financial losses
• Data analysis: AI services can be used to analyse data on tenant satisfaction, occupancy rates, and other factors to help housing associations identify areas for improvement and make informed decisions on future strategies

For those in the housing sector, introducing AI into your offering may seem daunting, but done well, a tenant-first approach that provides seamless self-service touch points along their digital journey will, in turn, drive internal efficiencies, a happier workforce and satisfied tenants.

Images: Orlo, Possessed Photography and Alex Knight