Design, maintenance and security, AI is an underused 'boost' in real estate

From the personalisation of buying and selling to maintenance, from tenant-owner communication to comfort management. Too often seen only as a tool to sell luxury homes or introduce expensive solutions on the value side, artificial intelligence is indeed a boost, but at the service of all real estate. Above all, of those objectives of efficiency, savings and responding to the needs of those who need an economically and functionally accessible home. The Efl Spring Conference 2024, the annual event of the European Federation for Housing, a network of 70 institutions and companies present in 19 countries, committed to the promotion and realisation of accessible and sustainable housing with more than 1.3 million real estate units built or managed throughout Europe, was held in Turin in recent days.

"According to the latest surveys conducted by real estate advisory companies," explained Alex Marchesini, ceo digital of Planet Smart City, "more than 80 per cent of investors and developers have shown their intention to increase the budget allocated to digital over the next three years (a budget that already stands at more than USD 4 billion globally). Indeed, there are already many technological solutions dedicated to the world of real estate, both for the design, management and maintenance of buildings. But globally, there are only 500 companies providing AI-based services to real estate that are producing value in terms of improving efficiency and reducing costs. A seemingly large number that is nevertheless very small compared to the size of the market'.

Despite this, applications of generative AI in the real estate sector are still in their infancy. The largest use cases concern assisting communication with customers in lease and property management (such as chatbots to handle tenant queries), generating floor plans and blueprints, and summarising unstructured documents to create reports.

To enable the proper application of digital technologies to traditional real estate, it is necessary to start from an analysis of the needs and requirements of the surrounding world. In order to do this, it is necessary to carry out very in-depth cognitive investigations of each individual need, breaking them down into the different market segments in which one will potentially operate (from affordable to midmarket, to luxury, passing through office, commercial and hospitality, to name but a few). Each of these segments has different needs that need to be studied and explored in depth before identifying the most suitable digital products for each segment. In this context, artificial intelligence, both predictive and generative, represents a very powerful tool to support this operation. Not only that.

Predictive intelligence,' said Marchesini, 'through the prospective analysis of residents' data, allows for the improvement of the customer experience and, in the long run, for the availability of an enormous data base that can potentially be monetised by the managers of large real estate complexes. In fact, the data collected on people's habits and consumption over the course of their life in a condominium make it possible to build predictive algorithms that anticipate residents' behaviour. This mass of (anonymised) information can be a gold mine, for example, for utility companies that will be able to predict where and how their customers will consume energy, gas and water. The same applies to local authorities with a view, for example, to environmental protection and the reduction of CO2 emissions. Not only that. Through the use of generative artificial intelligence, it will be possible to support the work of community managers in the automatic creation of content for residents or between sales teams and potential buyers. These are, in this case, simple products, but the application of AI can also be deployed in complex projects. Such as the predictive analysis of the consumption of flat blocks or individual flats by generating a real-time database for districts or households that can optimise daily behaviour and make consumption more efficient. From things as small as opening or closing curtains or windows, to the best time to run household appliances, to condominium irrigation linked to weather forecasts, all the way down to district and neighbourhood activities".