In THE ever-evolving landscape of real estate technology, innovations such as virtual reality/augmented reality, blockchain, the Internet of Things (IoT), and mobile applications have enhanced the operations and strategies of real estate players. However, generative artificial intelligence (GenAI), in particular, has captured considerable attention for its transformative potential.

This emerging technology has much implication and presents huge opportunities for real estate market players, and there will be many actionable steps that can immediately be taken.

Importantly, GenAI has democratised access by enabling a plug-in environment, thus allowing the integration of external data and adaptation to diverse contexts with minimal coding. This will greatly reduce the time and cost required to adopt GenAI models, enabling industry players to explore new use cases rapidly.

Redesigning real estate operations

One of the key areas where GenAI can make a significant impact is in the design and optimisation of space functions. By leveraging AI to predict the demand and needs of commercial spaces, real estate professionals can gain insights into productivity, employee/tenant retention and space planning.

GenAI opens the door to creating plans that not only optimise space, but also align with occupiers’ preferred style and requirements.

In terms of business transformation, GenAI offers unparalleled opportunities to streamline customer relationship management, property management, and legal processes.

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Inefficient systems can be overhauled, reducing resources and time spent on tasks such as summarising lease agreements and handling complex tenant requirements. Gen AI can even help in the negotiation of leases based on tenant characteristics.

Industrial assets can also undergo a significant transformation through the predictive capabilities of GenAI. From predicting product demand to optimising logistics, GenAI can drive productivity improvements in critical areas such as lease-writing, valuation and legal processes. This not only streamlines operations but also reduces the need for extensive warehousing.

Moreover, GenAI has the potential to create operational cost savings through intelligent buildings. These buildings, equipped with AI automation for features such as heating, ventilation and air conditioning, lighting, alarms, as well as security, present a futuristic approach to property management.

Additionally, the integration of GenAI with chatbots can lead to further operational cost savings in consumer-facing applications at hotels, retail spaces and residential buildings.

Investment opportunities

As the demand for high-performance computing associated with AI workloads continues to grow, data centres are poised to play a critical role. GenAI’s influence on data centre demand is expected to be significant, with accelerated adoption of high-performance computing and incremental space needed for the storage of training data.

Investment opportunities arise with the need for upgrading existing data centre facilities, or the development of new ones to accommodate the high-power-density requirements (AI-capable data centres require up to 10 times more power than normal ones), more efficient cooling systems, and increased data storage requirements. A case in point is the partnership between Singtel and Nvidia to revamp the telco’s data centres under a new unit, Nxera.

The use of GenAI is already transforming the real estate investment landscape. Real estate investment professionals have the opportunity to utilise GenAI for parsing unstructured data, evaluating the performance of properties, and assessing existing lease terms.

For instance, when selecting an optimal mall for investment, the algorithm can be provided with information such as catchment and household income within a specific radius.

Similarly, in the case of investing in a warehouse, the algorithm can consider factors such as e-commerce volume in the locale, proximity to residential areas, and accessibility to ports or airports.

This data-driven approach facilitates a more informed analysis of available properties, enabling the prioritisation of assets for deeper exploration and determining appropriate pricing strategies.

Increased real estate demand in tech hubs

A noteworthy trend is the emergence of global AI hubs. Markets characterised by a concentration of AI talent, such as tech hubs, innovation centres and universities, are expected to witness increased demand for infrastructure and real estate to house AI-related firms.

To illustrate, OpenAI has declared London as its inaugural international hub for AI technology and policies. Hsinchu in Taiwan, hosts an AI-focused business park serving as a tech hub, and is home to leading chipmakers globally. Shanghai is intensifying its AI investments, including the establishment of a significant computing centre in the coastal Lingang New Area, responding to the rising demand propelled by GenAI. Singapore, demonstrating its commitment to becoming an AI hub, has launched an updated National AI Strategy aimed at developing AI-related talent, models and infrastructure.

Another industry that could ride on the tailwinds of GenAI is the semiconductor industry, which is central to the field of AI and pivotal in powering AI systems.

The semiconductor industry is the largest manufacturing segment for Singapore, contributing more than 80 per cent of the country’s electronics output. With the renewed focus on AI, more semiconductor players are set to make more investments here, thereby increasing the demand for semiconductor facilities and high-specification factories or business park space for ancillary businesses. For example, chip giant Nvidia will potentially announce some large investments in Singapore on the back of its AI ambitions.

With these trends running, companies and investors could strategically position themselves at these hubs to fully harness the expansive potential presented by GenAI.

Adopting GenAI strategically

It is critical to approach the adoption of GenAI with a strategic mindset, to determine if the task is technically feasible and creates business value. Standardising data, adopting database-driven systems, and building engineering teams will then be necessary to ensure effective implementation.

For instance, an AI tool that has undergone training using a building’s historical maintenance requests can come up with the appropriate times for repair and upkeep. Similarly, a tool trained on the operating metrics of a real estate portfolio can provide insights about performance, aiding in investment decisions and reporting, including environmental, social and governance (ESG) monitoring.

In commercial buildings, IoT sensors and computer vision applications can offer insights into space utilisation. Tenant apps and dashboards can serve as valuable data sources; information such as the type of amenity space booked by a residential tenant, the stores patronised by a shopper, or the services required by a tenant can be gathered and organised for further analysis.

However, supporting infrastructure for AI clusters, including advanced data centres, robust energy grids and connectivity infrastructure, has to first be enhanced to support the growing use of GenAI.

Despite the transformative potential of GenAI, there are important considerations and potential challenges. GenAI is a nascent technology, and there are questions surrounding biases in training data and the appropriateness of certain use cases.

Risks associated with unintended consequences and compliance issues must be carefully weighed, particularly in areas with high stakes, such as emergency response, data privacy, long-term leases or investment decisions.

As real estate continues to embrace technological advancements, GenAI could take centre stage; it presents unprecedented opportunities for innovation and efficiency. Industry players can reshape their operations, unlock new strategies, and reap immense benefits from this technology.

The writer is head of research at Colliers, Singapore