Everyone knows that artificial intelligence (AI) is going to transform the world as we know it, yet understanding exactly what that implies is a hard endeavor at this point. In JLL’s recent Global Real Estate Technology Survey, machine learning and generative AI were identified by respondents as the second and third most impactful technologies for the future of real estate. Yet, intriguingly, these technologies were ranked at the bottom of the list in terms of respondents’ knowledge of them.

Technology ranked by expected impact on real estate and level of knowledge
Source: JLL

In this article, we explain how AI, and generative AI, in particular, is going to transform real estate, keeping in mind that generative AI in the real estate market is projected to grow from its current value of USD 351.9 million to USD 1.47 billion by 2032.

“Gen AI represents a fresh chance for the real estate industry to learn from its past and transform itself into an industry at technology’s cutting edge.” – McKinsey & Company

Generative AI in real estate market size from 2022 to 2032 (in USD million)
Source: Precedence Research

1. Real-time valuation and predictive analysis

Given the substantial capital involved, each decision to buy or sell real estate carries immense weight. Fortunes can be won or lost depending on the investment or the timing of the sale. Unfortunately, however, price data can be weeks if not months old – and that’s in widely covered markets. Within smaller markets, it can be literally impossible for you to get the information you need for timely decision-making.

AI steps in as a solution, as it can analyze data from a million different sources and apply logic to the analysis. It effortlessly handles data points that human analysts might struggle to compile and interpret. This includes diverse inputs like satellite imagery tracking foot traffic, weather patterns, census statistics, Instagram visuals, public transportation metrics, Amazon sales figures, and local government data.

Contrary to humans, AI can do these things in the blink of an eye. As soon as new data becomes available, AI can provide a swift analysis, eliminating the need for prolonged waiting periods.

Moreover, AI continually learns over time, constantly refining its model. With sufficient data and time, it can crack even the most complex real estate markets. Some AI real estate valuation models are now recording a staggering 98% accuracy in their estimations of sale prices, indicating their capability to predict future valuations with relatively high precision.

This makes the job of an investor a lot easier. Indeed, AI enables investors to gain deeper insights into their current positions, scout new opportunities and potential risks, and strategize for the future.

2. Personalized insights

AI models not only have the capacity to train on web data but also possess the ability to adapt and learn an investor’s preferences. This allows AI to provide data and insights tailored to investors – similar to how AI algorithms can recommend a product, song, or YouTube video to you based on your past behavior.

This personalized approach adds an extra layer of analysis on top of the macro- and micro-analysis that investors already use. For instance, consider an investor who initially selects a country based on economic fundamentals and population growth, and then narrows it down to a specific city or neighborhood. Once this is done, AI can simply jump in and rank general strategies or actual investments in that neighborhood based on the investor’s previous experiences and past successes.

It’s basically like having a powerful personal assistant who has worked with you and thousands of other investors worldwide for numerous years, but in this case – he or she knows every single detail, with no room for human error.

Some companies have found that AI-driven recommendations can increase net returns by up to 3% annually. Over time, this seemingly marginal improvement can compound significantly, leading to substantial gains.

3. Digital twins

In addition to the above, AI can also transcend observed data, delving into real estate markets and opportunities through digital twins – virtual models of buildings, neighborhoods, cities, or even whole countries that interact with real data. This concept goes way past generations of computer-based simulations to build detailed and interactive models.

Notably, a digital twin of Zurich already exists, and ETH Zurich is now building an open-source digital twin of Switzerland as a whole.

The main benefit of digital twins is that they can be used for simulation analysis. Humans and AI can run countless simulations using digital twins to understand how they’ll react to different scenarios and inputs. This provides simulated data that can improve the accuracy and predictive power of AI models, propelling them further than those that rely solely on previously available data, which is no guarantee of future performance.

For example, imagine if you wanted to understand the impact of an increase in the frequency of floods in Bern’s old town on real estate prices and maintenance. While historical data may be limited, AI leveraging a digital twin of Bern could offer insights across a wide range of scenarios.

In light of the above, it’s obvious that the potential of digital twins is tremendous. In fact, according to the “Global Digital Twin Market” report by Research and Markets, the global market for digital twins is expected to reach USD 110.1 billion by 2028, growing at a CAGR of 61.3% during the forecast period.

Digital twins market forecast for 2024-2028 (in USD billion)
Source: Research and Markets

4. Automated property management

Real estate investors who still opt for the traditional “buy-to-let” model spend a lot of their time interacting with tenants, real estate agents, staff, tradesmen, and utilities. Unfortunately for them, they’ve failed to consider that AI chatbots like ChatGPT can automate a large portion of text-based interactions, proficiently handling full conversations with users almost 70% of the time.

AI can track property listings and determine an optimal marketing strategy. Moreover, it can then sort through tenant applications – quickly identifying the best tenants – and can even prompt them for more information. Even after tenants have moved in, AI can track payments and handle all their day-to-day requests. At the same time, of course, any major or unusual issues would be flagged for the investor’s immediate and direct attention.

What’s more, according to JLL’s 2023 Global Real Estate Technology Survey, 91% of tenants are willing to pay a premium for tech-enhanced spaces. Over our course at Le Bijou, our digital concierge service “James,” backed by augmented intelligence – a subset of artificial intelligence – has also garnered substantial positive feedback.

AI extends its capabilities even further by using Internet of Things (IoT) devices to monitor properties in real-time – a leaking water boiler or flickering light, for instance, can automatically trigger a service request to a plumber or electrician. Likewise, AI can optimize water and room temperatures to maximize guest comfort while minimizing costs.

5. A personal guide for laws and regulations

A significant expense in real estate investing often involves hiring lawyers to understand national and local laws and regulations, with fees typically charged on a per-minute basis. Next comes the numerous back-and-forth with local governments over plans and regulations.

Once again, AI can come in and save the day. Believe it or not, AI can read and summarize applicable laws and regulations and even answer questions like a real-life lawyer. This can potentially save investors considerable time and thousands of francs. Although the necessity of legal assistance for contracts and conveyancing remains, and interactions with local officials are pretty much unavoidable, investors can diminish the frequency and duration of these engagements with AI.

Is there a data challenge?

It’s no secret that generative AI relies on large amounts of data, and at the moment, there are few barriers to acquiring such data.

That said, several groups of artists and writers are currently suing AI companies for copyright infringement. For instance, in October, a group of US authors, including a Pulitzer Prize winner, dragged OpenAI to court.

In the same vein, several jurisdictions, including the EU, are proposing stricter rules for AI that will include regulations around data training. As a result, AI companies may find it harder or more expensive to train their models with the depth and breadth of data they use now. Companies and institutions with valuable datasets will therefore very probably start to explore avenues for monetization.

“We want a list of the public disclosure of the material that is being used to train it [AI] because [authors] can go through other legislations and avenues to try to get paid for what is being used without their consent.” — Brando Benifei, Member of the European Parliament

Although this does represent a challenge, it’s not a show-stopper. As AI models create value, it’s only natural that they will share a portion of that value downstream. Further, the amount of data on the internet keeps increasing each year. In 2020, it reached 64.2 zettabytes and will soon pass 100 zettabytes — with a zettabyte being equal to a trillion gigabytes. As we move even deeper into the era of Big Data, AI models will have access to more data pools, even under more stringent regulations – and unlike human users, AI can access data from a nearly unlimited amount of sources.

“There were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every two days.” — Eric Schmidt, former Google CEO


While many AI models are still in their infancy, their impact on the real estate industry is already evident among those at the forefront. Yet, looking ahead a decade, AI’s integration in real estate will become indispensable, seeming like literal magic compared to today’s standards.

Hence, “today” represents a point of opportunity for those looking to invest in real estate with AI or for real estate investors who want to leverage AI to gain a strategic advantage over their competitors. In any case, one thing is crystal clear: the real estate industry can no longer afford to ignore AI.

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