Where is AI going in the property sector and what are the benefits & potential risks?

Property firms use AI-powered predictive analytics tools to forecast property market trends, identify investment opportunities, and predict property values.

These tools analyse large datasets including historical sales data, demographic information, economic indicators, and even social media sentiment to provide insights into market dynamics.

There is significant benefit in this, however, there is much to be said for the experience and knowledge of regional property agents on the ground too.

AI is also used in property management systems to optimise building operations, enhance energy efficiency, and improve maintenance processes.

Smart building technologies such as IoT sensors, predictive maintenance algorithms, and automated HVAC systems are integrated with AI platforms to monitor building performance in real-time and proactively address issues.

In a similar way, we use our own tools to support clients with the management of their property portfolios through a cloud-based Tenant Portal, facility management tool, Elogs and MRI Software to give clients data insight, risk management and convenience in the management of their properties / portfolio.

AI-driven virtual assistants and chatbots are being deployed by some commercial property companies and estate agents to enhance customer service and streamline communication with clients.

These tools can do everything from handling inquiries, scheduling property viewings, and providing personalised recommendations, to assisting with the buying or renting process.

However, what this sort of service also risks, is that removal of the ‘people experience’ which can really matter.

AI algorithms are being used by some companies to automate property valuation processes, providing more accurate and efficient assessments compared to traditional methods.

Machine learning models trained on large datasets of property transactions can analyse various factors such as location, size, amenities, and market trends to estimate property values.

However, AI should not be relied upon solely in the production of property valuations. These ought to always be thoroughly reviewed for accuracy by the boots on the ground. You cannot remove the importance of human knowledge around the specifics of each property.

Around for some time now, AI-driven recommendation engines are being employed by property listing platforms to deliver personalised property suggestions to users based on their preferences, search history, and behaviour patterns.

These recommendation systems leverage machine learning algorithms to analyse user data and identify properties that match their criteria. However, what such systems don’t do is offer up a potential curve ball option that they may not have thought of.

Again, this is where there is true value in a property agent who spends time in getting to know a business and its culture and might throw in a potential property that they know would work but might not necessarily be within their geographical specification.

AI is also being used for risk assessment in property transactions, including mortgage lending and insurance underwriting. Machine learning models analyse factors such as borrower profiles, property characteristics, and market conditions to evaluate the likelihood of default or insurance claims, enabling more informed decision-making by lenders and insurers.

Again, the importance of first-hand investigation by a local surveyor who knows the property, or who is able to monitor ongoing works, cannot be underestimated.

AI-powered VR and AR technologies continue to transform the way properties are marketed and showcased.

Virtual tours and 3D property visualisations created using AI algorithms provide immersive experiences for potential buyers or tenants, allowing them to explore properties remotely and even visualise themselves living or working in the space.