AI and the evolution of proptech

“Proptech is now widely adopted across the whole real estate value chain, so we already had a solid foundation for incorporating AI technologies across the industry,” Wang says.

This isn’t to discount the potential of AI, which is ranked among the top three technologies expected to have the greatest impact on real estate over the next three years by investors, developers and corporate occupiers, according to JLL’s Artificial Intelligence: Real Estate Revolution or Evolution report.

Capable of analyzing several large data sets at once, AI is supporting decision making by creating tailor-made listings of properties based on a client’s preferences and previous activity, as an example. Generative AI, which learns patterns and behavior of input data to produce new content, is being used to respond to customer queries all day, every day.

Still, digital transformation began impacting real estate decades ago with property management software, customer relationship management systems and financial analysis tools.

From there it has only expanded further. In 2021, JLL found that the number of proptech start-ups had tripled over the previous decade. The first six months of 2021 had seen a record $9.7 billion in funding activity for the sector, propelled by the pandemic.

While the surge continued through to 2022, funds have tailed off in 2023, with PitchBook data recording US$2.2bn in proptech venture capital deals globally to May. Nonetheless, confidence in the sector remains high.

“There are now technological solutions for almost every aspect of real estate functions, including investment management, design and construction, building and facility operations and portfolio management,” Wang says.

What’s next for AI

However, with over 500 companies globally currently developing AI-powered services relevant to real estate, AI is set to wield the biggest influence. In fact, the total capital raised to fund AI-powered Proptech reached $4 billion globally in 2022 – twice that raised in 2021, according to venture capital and private equity research firm PitchBook.

The early adopters are already reaping financial benefits.

For example, U.K. investment firm Royal London Asset Management has used JLL’s AI- powered Hank technologies to improve its heating, ventilation and air conditioning (HVAC) operations and overall energy efficiency in its 11,600 square meter (125,000 square feet) Birmingham office building. Since the start of 2023 it has achieved a 708% return on investment, saved 59% in energy output, and reduced its carbon emissions by 500 metric tons per year.

“AI technology is also used to analyse data from the building management system to understand the performance of the equipment in that building, identifying clearly what might need to be changed or maintained,” says Carolyn Trickett, Growth Principal at JLL Spark Global Ventures, the corporate venture arm of JLL and part of the JLL Technologies division focused on investing in strategically relevant technology to optimize the needs of JLL’s clients.

Another strength of AI is its ability to rapidly analyze large amounts of data, even from different data streams, something that can more efficiently inform management decisions.

Take the work of VergeSense, spearheaded by JLL Spark, which uses optical sensor technology combined with AI to offer insights about how buildings are used.

“Which desks are used most frequently? How often are meeting rooms used? What times do people arrive and leave?” Trickett says. “In a post COVID-19 world with an increase in hybrid working, this can help analyse the space needs of a company.”

AI can also work 24/7, and generative AI, which uses advanced algorithms to generate content like the answer to customer queries, can be trained to respond to out-of-hours queries, increasing satisfaction from existing tenants, or the potential conversation rate of prospective ones.

While AI technology and its capabilities are still in their infancy, there are some legitimate concerns that any early adopter needs to consider.

“The regulation landscape for AI isn’t moving quite as fast as the technology,” Wang says, “So you should consider potential risks in cybersecurity or data security when considering implementation.”

She adds: “We are at a critical point for businesses to start thinking about the pain points AI technology might be able to help you with and how you might need to refine your processes or technology to realise the most value from it.”