AI in Real Estate


Artificial Intelligence has been a buzzword in the real estate industry and a growing number of companies now offer services backed with AI. According to PwC, AI-based innovation will lead to 10.3 percent growth in UK GDP by 2030 as a result of AI. But what exactly does AI do?

To answer this question, we need to discuss two things – computing power and alternative data sets – because AI is all about analysing data sets.

In 1965, an engineer called Gordon Moore predicted that the power of computers would double every two years. In 1975 this was proved to be true and Moore’s law was created. According to research by Open AI, the amount of computing power today increases every 3.5 months. It is now 50-60 times faster than Moore’s law and since 2012, the metric has increased by 300,000-fold. This has led to key progress in applications such as speech recognition, computer vision, pattern recognition and much more. At the start of 2017, it cost $10,000 (£7550.05) to classify one billion images on the latest computers whereas by the end of 2019 it was only 3 cents (3p) which is exponential growth at an incredibly fast rate compared to Moore’s law.

We now have significant computing power at our fingertips to analyse anything we want. This means we can move away from our flawed ways of thinking about data and only choosing what we believe is relevant. By moving away from out of date, aggregated data, we can start analysing real time information that provides actionable insights.

However, computing power is only one side of the potential of AI. The disruption that AI is expected to cause has a lot to do with the data that is being analysed. The sheer volume of data that’s generated, and therefore is available, is on a steep upward curve. 90% of all the data in the world has been generated in the last two years, which means there’s data available for nearly anything you can think of.

How is AI used in Real Estate?

There are two types of AI that are applicable in Real Estate. Let’s start with the easiest to understand, Narrow AI. This type of artificial intelligence is about analysing deep detailed data and is mostly used to better understand property operations.

Buildings are becoming “smart buildings,” which in layperson’s terms means there’s a lot of meters and sensors that will measure the use of the building and its equipment. Think of smart thermostats, locks, lifts and doors that are in place to measure when units and equipment are being used and how.

The data generated from these meters and sensors helps in two ways – to optimise operations, the use of the building and its spaces, and to effectively measure planned maintenance and investment decisions.

Out of the generated data, you can even begin to analyse how many times a lift can be used before it needs maintenance, or even which brand of lift will be the best economical choice, as it provides expected usage data for new and renovated buildings.

Broad artificial intelligence is the same concept, but this is referring to using alternative data sets for broader, or more high-level, management decisions. The complexity with Broad AI is taking into consideration which data you need as well as the human comprehension of the analysis.

To answer strategic questions, such as rent level developments for offices, you need to choose the right variables or data that’s relevant and then begin gathering this information. However, with uncertain data and unprecedented times, it may not be humanly possible to predict this information today. Although, with the potential competitive edge that the real estate investment management industry could gain, they will start pushing for this ability to advance rapidly to enhance predictions as soon as possible.

It’s a matter of time until this predicted data will be available in high-quality, and within the next 7 – 10 years we should expect to see this information become the norm. The computing power is already available and there are huge data sets that are accessible as well. However, developing the calculations, aka algorithms, is the missing link.

If you look at the technology you readily use, such as the data from your car navigation system, you’ll notice how it’s changed completely throughout the years from basic directions to live traffic and weather information. We expect to receive exact travel time predictions from A to B, and we’re beginning to want it to take anything else into consideration that might be a factor in us arriving on time.

The way we gather data and utilise AI is evolving rapidly, and as an industry, we need to be ready for that change if we want to keep up with the future of real estate. Every piece of data we gather can be effective and help improve our business decisions, but we need to have the right strategy in place to begin using it.

This article was originally posted in German on Immobilien Manager.