Gemma Leonard, Head of Development at international law firm DAC Beachcroft, examines the evolving role of AI in residential development.
Across the property industry, the residential sector has perhaps the greatest potential for utilising AI to enhance processes from development through to marketing, management and customer service. The proliferation of the build-to-rent sector has added another dimension to this as its relationship with occupiers needs to provide services across a much longer timeframe than in the build-to-sell market.
Where and what to build?
AI systems can greatly assist in design optimisation of residential construction in a number of ways: analysing design plans, identifying potential structural flaws, enhancing space utilisation, and prompting improvements before construction begins -all saving time and money on potential reworks.
On the supply side, AI is helping developers to rapidly sift through the planning landscape to ascertain where their effort maybe best directed.
Last Autumn, The Ministry of Housing, Communities and Local Government Digital Planning Programme partnered with Faculty AI, a specialist in applying AI and technology, on a project to explore the potential of AI to extract specific information from planning documents.
The partnership created a chatbot that can pull out important information from local plans and uses the data in these plans to answer questions based on what it finds. The chatbot correctly answered questions about how many homes were to be built within a specific time frame 59% of the time, and during the lifetime of the local plan (normally 15 years) – 76% of the time.
This type of approach is now being mirrored by AI providers like Planda which uses algorithms to analyse vast amounts of planning data to provide predictions on application outcomes. It aims to reduce the time and complexity involved in planning applications by identifying potential issues and providing guidance early on.
Further down the supply chain, AI-powered tools, such as Procore, have enhanced project management in the residential construction space through gathering and analysing data to create targeted timelines, identifying potential bottlenecks, and automatically adjusting schedules based on changing conditions.
Who’s my occupier?
However, before developers get to the planning stage with projects – whether they are targeted at the rental market or owner-occupiers – they need to ascertain which locations will be receptive to their projects. In this respect, the economic and demographic identity of locations is an increasingly important aspect to bringing precision to the process. Crucial data on demographics, average property/land price, along with earnings and wider economic prosperity all count towards the decision making of residential developers.
The new spatial intelligence platform, EvaluateLocate, tracks the economic identity and vitality of every UK location from postcode district level outwards. By giving access to more than 100 metrics, developers are able to explore where their product may be best received. The platform can also match the identity of completed development locations with other places in the UK which have the same or similar economic and demographic characteristics and therefore may be suitable for similar projects.
Capturing the market
Whether in the owner or renter market, competition is fierce across the residential market and with cost inflation having eaten into margins, the need to successfully capture in the shortest time is pivotal.
AI is now moving to the heart of the market engagement process. Now familiar tools such as ChatGPT and OpenAI are enhancing the speed with which marketing content can be generated while products such as CubiCasa boasts that it can generate interactive floorplans and virtual tours in minutes which can enable occupiers to better understand what a scheme will provide.
Immersive images and interactive virtual tours of developments are not particularly new in the residential sector but it is the speed and economy that AI is bringing to their use which is revolutionising the process of market engagement. The number of AI virtual tour providers is also growing with AgentUp, Liv by Unify, RICOH360 and Real Space 3D all having entered the sector recently.
The virtual manager
In the rental sector, the management of residential assets is another area where AI can deliver substantial time and cost savings. For property managers, integrating generative AI into their processes can have a transformative impact on efficiency and precision.
AI technology is being leveraged to help improve the tenant screening process, helping landlords find more reliable tenants, boost tenant retention rates, and minimise costly void periods. AI-powered tenant screening tools can automate the retrieval and analysis of data, quickly and accurately analysing large quantities of tenant data, including credit scores, criminal records, financial history, and rental history.
All of these processes are labour-intensive, and have historically relied on teams of people on hand to manage queries, complaints, and tasks across large property portfolios and holdings.
ResidentialAI – part of the Elise AI offering – is a product that offers resident services, assists with raising maintenance tickets, and automates lease renewals while also reducing tenant delinquencies. This corner of the market is getting increasingly crowded with platforms such as LandlordVision, ArthurOnline, Aiden and Spaciable among those competing for a share of a huge and growing market.
The choice challenge
While it’s clear that AI can deliver substantial innovations across the residential property sector, the proliferation of competing platforms may mean that the biggest challenge is which AI to choose. Ultimately, there will be winners and losers among the AI-powered solutions on offer to the residential sector and the picture will clear, but until then selecting which tech to go proceed with will require care.
