The AI Future

Published on
April 11, 2024
March 21, 2024

Artificial intelligence (AI) has garnered a considerable amount of attention in the media within the past few years, ranging from glowing editorials to scare-mongering pieces. The broader public is becoming more aware of the potential applications and implications of the technology that is developing at a tremendous rate.

AI is a broad umbrella that encapsulates a few different terms in advanced computing, such as machine learning and deep learning frameworks, referring to the current stage of advanced computing rather than a specific technology type or resource. Technologies such as large language models (LLMs), generative AI and the theoretical artificial general intelligence are all subsets under the umbrella term of AI.

AI has massive implications for society, affecting how we live, consume and work, among other impacts. It enables process automation, with the potential to be able to replicate many tasks currently performed by skilled humans at work. A report from Accenture estimates about 40 percent of all working hours could be affected by AI LLMs such as ChatGPT-4. That is with the current generation of AI. With accelerating progress and innovation within AI, it could become more than feasible for businesses to reduce costs by directly replacing employees with AI.

At a recent conference in the Middle East, former UK Prime Minister Tony Blair highlighted that AI currently has access to 300,000 years of knowledge working at an approximate IQ of 50 and is achieving traction. Its next variation will have the capability of a human at an IQ of 150. When the tech becomes the equivalent of someone at an IQ of 200, that is when we will see incredible usage. Married to this is the fact that, according to OpenAI, roughly 80 percent of jobs are exposed to AI disruption in some form. What is certain is that the future of work is uncertain for many of us.

Current AI Use Cases in Property

The property sector has long been ripe for tech enablement, given its historic aversion to the adoption of technology. AI has numerous potential opportunities to play a role in different stages of the property lifecycle and in the supporting ecosystem. One of the standout applications we are seeing in real estate is AI used for data analytics. There are two primary use cases — market data and building management systems (BMS). Big market data is allowing AI platforms to assist transactions through identifying investment opportunities, valuing properties, and pairing buyers and sellers based on preferences. In addition, AI is performing data functions in lead generation and sales engines, incorporating businesses’ internal data and external big data. BMS’ are increasingly integrating AI models into their platform to assist in occupancy forecasting, predictive maintenance and automating reporting functions.

These are all immediate applications of AI, feasible with the current generation of the technology. Over time, these systems will drastically improve in terms of accuracy and predictive capability. But, even with the current use cases available, AI is augmenting real estate-related processes, enabling businesses to make more informed decisions, optimize their portfolio and adapt space for optimal usage.

Consequences for The Future of Real Estate

The increasing adoption of AI will touch real estate from multiple angles, from how firms conduct operations to the actual availability of different property sectors. Forecasting the demand for property usage in the future based on nascent technology is a futile endeavor, given the rate of innovation in the space and unforeseen government policy and regulation. However, naturally, space demand will shift. As a result, some property types are expected to become less sought after and others to benefit from increased demand.

One of the largest concerns is AI replacing jobs. Even today, AI has replaced roles in Hollywood for script writing. Businesses will increasingly incorporate AI into their operations, and workforces will shift in size and dynamics, therefore affecting the demand for commercial offices. Along with other macro trends, such as remote work, AI will continue to drive the shift for more flexible office leases with shorter lease periods. Traditional businesses affected by AI are more likely to require smaller spaces, and five-day working weeks could become unusual, resulting in people having more free time or varied portfolio working roles. As a result, demand requirements for traditional large commercial offices will alter. Offices will be used more for collaborative meetings and for fostering organizational culture and brand. Offices will increasingly follow the trend of retail in how flagship stores are utilized, where premium real estate will have higher demand, effectively demonstrating presence in a market to bolster brand optics and staff retention.

AI will also affect office demand from a tenant attraction perspective. Tenant attraction and retention will be aided by AI servicing and value-add through tenant engagement apps, space usage analytics, and green certifications gained through AI-assisted energy management and BMS. Furthermore, with real estate operations becoming streamlined and optimized through AI — both for business and consumer applications — space acquisition and the process surrounding it will become easier, faster and more accessible than ever before, potentially enabling more transactions and market activity.

Away from commercial offices, the demand for data centers will grow to facilitate the rapidly increasing rate of data capture and computing need, caused by rising usage of technology such as AI. McKinsey & Co. estimates U.S. data center demand will increase by about 10 percent a year until 2030. Though innovations in server technology and advanced computing will help steady the curve in demand for space, meaning data centers will be able to house more server capacity, this will reduce the amount of space required from a computational perspective. On the assumption people will have more free time in the future, public and retail space will get more usage. We see new space types emerging, enabling different forms of entertainment, such as complete metaverse immersion or other tech-enabled entertainment spaces such as the Sphere in Las Vegas. Digital properties and marketplaces will become more practical based on increasingly more feasible metaverse and digital reality use cases.

Although AI has generated a lot of fear regarding the effect on demand for real estate, the technology will also have many benefits, assisting a needed transformation of the property sector. City planning can be conducted with greater insights provided by AI and big data. This means the environment we live in could adapt quicker to the needs of the population, built on optimal usage. AI can provide 24/7 support, automating logistics and network functions in concepts such as 15-minute cities, where all individuals in a city population have work, provisions and education-related property available within 15 minutes of their residence. This is a trend factored into many large developments such as The Line, a 106-mile linear smart city that is the integral part of Saudi Arabia’s NEOM project. Furthermore, increased visibility of demand through AI market capture will drive real estate development, along with the insight from AI-integrated BMS providing a natural pathway to utilizing space smarter and more efficiently.

The AI Bottom Line

AI will affect space demand globally, first starting with major economies that will be the early adopters when they implement the technology. In a second wave, this will move to neighboring regions as innovation waterfalls. It is unclear how much it will affect demand in terms of exact volumes, but it will undoubtedly influence demand requirements, increasing space efficiency and shifting the usage of spaces. We see this as a major trend affecting commercial real estate during the next 10 to 15 years, along with some other large, related macro trends such as increased urbanization, environmental concerns and uncertain economic outlook. The nimbler operators (as always) will evolve and adapt earlier, whereas technology laggards may struggle to maintain relevance in a changed landscape.

This article first published in Institutional Real Estate Real Estate Asia Pacific.

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