At the height of the coronavirus pandemic, tens of thousands of Britons found themselves racing against the clock to complete their home purchases, as a deadline loomed for the expiration of a property tax relief measure. Offering savings of up to £15,000, the relief had spurred a surge in transactions that overwhelmed estate agents, surveyors, and lawyers involved in the cumbersome process of property transactions. 

Seeing the strain on the system, the UK government announced an extension of the stamp-duty ‘holiday’ by a few months. The decision underscored the pressing need for digitisation in real estate, even today. Indeed, ‘proptech’ can streamline processes for buyers, sellers, tenants, and landlords alike.

Compared to other sectors, such as banking or insurance, real estate has been slower to adopt digital technologies. This lag means that many processes within the industry still rely heavily on manual methods, paperwork and face-to-face interactions, which can be time-consuming and prone to errors.

Real-estate data, especially – such as geographical maps and traffic patterns – pose unique challenges. Unlike structured data commonly found in financial transactions (numbers in spreadsheets) property data often comes in unstructured or semi-structured formats, making it difficult to capture, organise, and analyse.

Consider blueprints, the intricate technical drawings that depict the layout, dimensions and specifications of buildings. Converting these physical blueprints into digital formats while preserving their accuracy and detail can be a complex and labour-intensive process. Nonetheless, such data is essential for effective decision-making, risk assessment and market analysis.

Enter artificial intelligence (AI), a game-changer for property that is also the driving force behind the new FutureFinance.AI Research Group that I lead at Warwick Business School. Thanks to a £1.25 million donation, the research group aims to utilise generative AI as a tool to improve the efficiency of real estate operations. 

The revolutionary potential of gen AI in data management

Generative AI (gen AI) is capable of performing a wide range of tasks and adapting to various contexts, unlike legacy or ‘narrow’ AI systems that focus on specific tasks.

With gen AI, the real estate industry can transcend the limitations of manual data management and interpretation, ushering in an era of unprecedented efficiency. Traditionally, that has been a labour-intensive and time-consuming process, one that involves gathering, organising, and analysing vast amounts of data from disparate sources.

However, gen AI can streamline this process by ingesting and processing data automatically. This means real estate professionals can quickly analyse complex datasets and extract actionable insights, saving time and effort.

What will FutureFinance.AI accomplish?

Warwick’s FutureFinance.AI group plans to build AI tools for integrating and processing diverse data sources – including drawings, blueprints, and surveys. Rather than simply digitising images or files, we aim to imbue real-estate data with deeper meaning and semantics. 

One key feature of the upcoming tools is their ability to represent data in formats that are easy to work with. Rather than presenting raw data or complex analyses, our platform will deliver insights in user-friendly formats that are accessible and understandable. This includes visualisations, summaries and interactive dashboards. The process involves extracting and interpreting the underlying context, relationships, and insights embedded within the data. By capturing the essence of real estate information, gen AI systems can provide more valuable insights for stakeholders. 

What’s more, FutureFinance.AI plans to develop an open platform, making such tools accessible to everyone in the real estate industry. This liberalisation of AI has the potential to foster innovation and level the playing field. Historically, real estate has been dominated by established players, but advancements in technology can foster greater competition and innovation. Ultimately, it can drive collective growth in a sector crucial to the UK economy. Commercial property alone contributes £137 billion annually, about 7%of the total gross value added. 

FutureFinance.AI’s platform is still under development and operates on the principle of “AI as a service”, meaning that AI capabilities are provided to users on-demand. This allows real estate companies to access advanced AI tools and technologies without the need for significant upfront investment. 

By offering AI-driven insights as a service, the platform democratises access to cutting-edge technology and empowers users to leverage AI to enhance their operations and decision-making processes.

New developments with AI models

A key aspect of this platform involves us obtaining sufficient training data to teach AI models to interpret and embed real estate blueprints effectively. This process requires curated datasets containing a diverse range of blueprints and associated metadata. Once trained, AI models can automatically analyse the data, extract relevant information, and generate descriptive summaries or insights.

The ultimate goal of the research is to automate design processes within the real estate industry. By leveraging AI, stakeholders can streamline tasks traditionally performed manually, such as modifying designs, interpreting blueprints, and generating design alternatives. This automation promises to accelerate project timelines, reduce costs, and enhance overall efficiency.

Job displacement is not a significant risk in the real estate sector, due to the focus on enhancing efficiency rather than replacing human workers. While some job losses may occur, the adoption of AI has the potential to lower barriers to entry for new market participants. This, in turn, can lead to increased job opportunities as new entrants bring fresh perspectives and solutions to the market.

Future trends in proptech

Looking ahead, in addition to AI, blockchain technology is a key focus area for FutureFinance.AI. One crucial aspect of property transactions is ownership documentation, and blockchain offers a secure and transparent way to record property rights. By leveraging blockchain for property documentation, the industry can streamline processes, reduce fraud and enhance trust among stakeholders.

Further research and development are needed to unlock the full potential of technologies like blockchain and AI. However, it is evident that these technologies have the potential to revolutionise the landscape in the coming years, fundamentally altering how properties are bought, sold, rented, and managed.

Authors from the Gillmore Centre of Financial Technology at Warwick Business School have kicked off the Gillmore Centre Series, which explores new innovations in fintech from an academic perspective. Keep an eye out for more articles from the Gilmore Centre to learn more about new developments in the field.