ARE YOU
PREPARED FOR AI?
Artificial intelligence could offer more than we expect. So how can investors position themselves to reap the rewards?
ARE YOU
PREPARED FOR AI?
Artificial intelligence could offer more than we expect. So how can investors position themselves to reap the rewards?
By Ian McGuinness, Head of Analytics de Knight Frank
Select any successful real estate developer from a previous generation and try to identify what made them successful.
Whoever you have in mind, their success probably depended largely on who they knew, which in turn determined how they found the best sites and accessed the funding to develop them. Success in this industry has always revolved around "first-hand" knowledge. That is why it is so exciting to be at the beginning of a revolution in artificial intelligence (AI), one that will allow us to make sense of vast amounts of information, something that a few years ago would have seemed impossible.
In fact, our AI-driven data processing capabilities will represent the biggest advance in productivity since the advent of the Internet, saving the average worker more than 100 hours a year, according to Google. In the UK alone, the company estimates that AI-driven innovation will create more than £400 billion in economic value by 2030. PwC projects that GDP will be more than 10% higher during the same period than it would have been without the technology.
Pioneers
Those investors who engage with AI early will be in a position to reap the lion's share of those gains. In real estate, in particular, technological advancement offers a unique opportunity to generate returns.
But first, some terminology. The popularity of large-scale language models, such as OpenAI's ChatGPT, might make it seem like AI arrived in 2023, but the natural language processing (NLP) technology behind these chatbots has been with us for several years already.
The genius of ChatGPT was its simple interface, which allowed hundreds of millions of people to get their first taste of what AI can offer.
PLN allows us to extract value from large amounts of unstructured text. Some readers may have experienced the frustration of manually moving data from a PDF to a spreadsheet so that it can be manipulated and analyzed for insights. AI automates that process on a large scale. These models can put words into context and make inferences in a way that the world is just beginning to understand.
Investors who engage with AI early on can reap the lion's share of those gains. In real estate, rapidly improving technology offers a unique opportunity to generate returns
View of the Future
We began experimenting with NLP four years ago by applying it to urban planning databases. It immediately became apparent that there was a wealth of information in the comments added by planners that was impossible to compile manually. Thus, we were able to track how businesses across the country were adapting to the Covid-19 pandemic, for example, by changing the use of their properties.
It became clear that PLN could be useful for finding development sites, especially when combined with other techniques. Knight Frank's Research Analytics Team has deep experience in data management, analytics and visualization. We view AI as a chain of processes that includes language processing, but also encompasses computer vision, classification and learning techniques that allow us to address data gaps and make accurate predictions.
If you could walk with me around central London right now, I could show you every available development site and its location in relation to lifestyle elements, such as top-rated schools, fine dining restaurants and private clubs. It could also tell you how many wealthy people live nearby, their property preferences and how much they can spend. With AI, all of this can be done during a chat at the Knight Frank offices.
Local Intelligence
These technologies become more interesting when applied to complex problems, especially during periods of high borrowing costs. The financial viability of retrofitting commercial buildings to achieve a better BREEAM or EPC rating varies depending on underlying values or rents. By feeding our models with the relevant data, we can generate accurate contours that indicate where investment is most likely to generate high returns.
One of many examples of scalability was our study of parking lots for the London Department of Levelling, Housing and Communities, who wanted to find out if any publicly owned parking could be put to more profitable uses, such as retail or residential. We studied over 30,000 parking lots and found that, although they were well connected by public transport, almost 70% did not appear to be suitable for a shopping center. When considering land value and redevelopment potential, we identified enough space to build more than 100,000 housing units, while retaining parking amenities that are vital to support commercial areas.
New Heights
Data is rapidly increasing and how real estate investors handle that amount of information is now one of their biggest challenges. AI will help capture "unique" opportunities, because only its computational power can fully resolve and scale the multiple physical, socioeconomic and environmental conditions that underpin success.
PLN, computer vision and machine learning techniques will play an increasingly important role, but they are still best combined with the skills of relationship building and forecasting, which have been used by successful developers for decades.
The abundance of information fuels the potential for a generation of real estate investors to reach new heights, if they can bring fresh perspectives and discern the signals among the noise. Returns will increasingly depend on the quality of the data and interpretation they have access to. Success is still about "first-hand knowledge," but that term doesn't mean what it used to.