How Artificial Intelligence is outperforming humans at real estate investment

AI outperforms humans in real estate

Elisabeth Kohlbach, CEO and co-founder of Skwire, informs us of how AI is transforming the real estate investment sector.

The worry caused by the coronavirus pandemic has understandably posed a challenge to the real estate sector across the UK – not least for investors, who are facing an uncertain immediate future for their portfolios and potential investment opportunities.

However, whilst Covid-19 will of course present challenges in the weeks and months ahead, new developments in technology relevant to residential property will still enable investment opportunities to be identified in the medium-to-long term.

In particular, powerful recent advances in Artificial Intelligence have improved the ability of investors to pinpoint high-yield investment targets. Moreover, AI can also uncover patterns too subtle or counter-intuitive for human analysts to notice.

It’s worth taking a closer look at both these areas to understand just how much AI is transforming real estate investment.

Identifying potential real estate investment targets

AI-enabled systems can now process huge amounts of data that no human being could trawl through manually. Whereas in the past an investor looking for a decent return would have had to rely on an army of local agents and/or analysts, thanks to AI-powered algorithms it is now possible to pinpoint high-yield investment targets with much greater speed and accuracy.

For example, at Skwire we use AI to evaluate the revenue potential of every single property coming onto the UK market, processing the entire country’s worth of available properties in real time to identify a list of the most promising investment opportunities. This shortlist can then be subject to further (manual) investigation and review.


Read More: Lavanda: How is technology democratising the short term rental industry?


It is this approach which enables investors to identify opportunities that will outperform the market. Indeed, using AI we have been able to process hyper-local data from a variety of sources – from hyperlocal geospatial inputs the rental price premium for a garden versus a balcony in a specific street, to geospatial inputs, to demographic shifts.

And what is truly transformational is that these AI-enabled systems do not need a property expert telling them what trends to focus on. Instead, the algorithmic method of clustering properties by similarity unearths patterns that investors may not even have thought of.

The hidden detail

Of course, experienced real estate investors know that there are particular factors, such as a large infrastructure project being greenlight for an area, that will increase capital growth potential. A second pattern investors are looking out for is smaller-scale neighbourhood regeneration driven by ‘organic’ demographic shifts rather than by planned large-scale public investment schemes. Take an independent coffee shop replacing a chicken shop as a classic signal of a neighbourhood on the up.

However, by the time the traditional investor notices the coffee shop on the high street, an AI-powered decision maker will already have made their move. To be precise, the AI would have spotted leading indicators, subtler signals such as demographic changes reaching a tipping point, which materialise before any physical changes on the high street appear.

Indeed, at Skwire we have used AI to uncover incredibly localised or even counterintuitive patterns that help assess the potential of an asset. For example, our algorithms identified where an (expected) slight rental yield premium for Liverpool waterfront flats over all turned into a surprising penalty along a short stretch.

It is by being able to process this level of granular detail that investors are able to de-risk investments and identify opportunities others have overlooked.

But without using AI, trying to identify these subtle yield-driving signals is not only time-consuming and resource-intensive, it also means that investors are already behind the curve. Looking out for signals like these means they are not catching an opportunity on the up, but chasing a trend that is already well underway – and priced in – by the time they have identified it.

With all of this it is clear that the power of Artificial Intelligence is already having a demonstrable impact on real estate investment. For many investors, it is not a matter of whether they will embrace AI, but when.


Elisabeth Kohlbach

CEO of tech-first real estate investment company Skwire.

Six ways to maintain compliance and remain secure

Patrick Spencer VP at Kiteworks • 16th September 2024

With approximately 3.4 billion malicious emails circulating daily, it is crucial for organisations to implement strong safeguards to protect against phishing and business email compromise (BEC) attacks. It is a problem that is not going to go away. In fact, email phishing scams continue to rise, with news of Screwfix customers being targeted breaking at...

Enriching the Edge-Cloud Continuum with eLxr

Jeff Reser • 12th September 2024

At the global Debian conference this summer, the eLxr Project was launched, delivering the first release of a Debian derivative that inherits the intelligent edge capabilities of Debian, with plans to expand these for a streamlined edge-to-cloud deployment approach. eLxr is an open source, enterprise-grade Linux distribution that addresses the unique challenges of near-edge networks...

Embracing digital AI recruitment without rocking the boat

Katherine Loranger • 11th September 2024

Artificial intelligence (AI) is set to become indispensable in business operations. For global enterprises, AI offers significant benefits by simplifying complexity and enabling confident decisions—when used in the right way. Those HR recruitment teams that seamlessly integrate AI technologies will optimise their recruitment practices and will have the opportunity to better realise their commitment to...

Why a data strategy underpins a successful AI strategy

Jim Liddle • 05th September 2024

AI and machine learning offer exciting innovation capabilities for businesses, from next-level predictive analytics to human-like conversational interfaces for functions such as customer service. But despite these tools’ undeniable potential many enterprises today are unprepared to fully leverage AI’s capabilities because they lack a prioritised data strategy. Bringing siloed and far-flung unstructured data repositories into...
The Digital Transformation Expo is coming to London on October 2-3. Register now!