AI’s Next Frontier Is Physical—CRE Shows What That Means

AI is transforming the world of commercial real estate (CRE), bringing us to the reality of even smarter buildings that don’t just react to their environments but interact with them. That’s precisely what today’s advanced AI, such as embodied AI, can do through robots and sensors, among other things. 

Today, technology ecosystems in property management are maturing faster than ever, with hundreds of companies offering AI services tailored to the real estate industry. According to JLL, 80% of real estate investors and developers plan to increase their technology budgets in the next three years.

Unlike traditional AI, which is confined to screens and software, today’s AI can move in the physical world and modify it, in the case of smart buildings. It’s an exciting new chapter in the AI revolution, taking the world by storm. What’s more, CRE is one of the main areas where this emerging technology shows tremendous potential to transform how we live and function in our surroundings.

Challenges plaguing the industry

Arguably, a solid foundation already exists for AI integration, but facility managers still face uncertainties around adoption. Part of that lies in a lack of understanding about how AI can be used to simplify and enhance building operations, with around 59% of facility managers struggling to develop adequate implementation strategies. For example, many site managers are well aware of incidents where smart HVACs have failed, causing damage, severe financial losses, and injury to humans.

A lack of interoperability is also worrisome, as the concept of new technologies that don’t integrate easily with existing systems is off-putting. Not to mention the costs involved with implementation, ongoing developer support, and staff retention. Moreover, fragmented systems prevent facility managers from easily keeping a finger on the pulse of energy consumption and operational efficiency.

Besides this, the data generated from smart buildings can be overwhelming to process and understand. Facility managers are likely to remain unwilling to adopt new solutions like AI if managing data feels like another time-consuming and costly task.

AI as CRE’s next frontier

In the CRE sphere, AI answers some of the most demanding problems, including reducing data overflow challenges, improving sustainability, lowering energy costs, predicting maintenance needs and failures, and connecting fragmented systems.

Recent insights from PwC show that 46% of CRE firms believe AI is set to transform operational management over the next five years. Smart HVACs help to satisfy this demand, as unlike traditional HVAC systems, they track energy use, adjust settings to minimize waste, and optimize performance. The overall result is lower energy bills and stronger efficiency; building managers can slash electricity costs by up to 30%.

The advancement in today’s AI is making those smart HVAC systems smarter. For example, it can aggregate data on factors like energy and water consumption into platforms for real-time analysis using AI assistants. Having immediate access to data, facility managers spot opportunities for better energy efficiency, whether making sure to use less electricity at night or pinpointing which parts of a building need less electricity based on foot traffic.

Taking this a step further, these solutions can create adaptive building environments with AI-integrated lighting, heating, cooling, and even occupancy tracking. This prevents unnecessary resource and energy use while reducing carbon footprints.

Tools like real-time monitoring and AI assistants can also notify building teams about equipment failures and provide immediate options for solutions or the cause of the problem. By doing so, AI is helping teams streamline day-to-day management and operations.

Integrating AI: A collaborative approach

Educating building owners, facility managers, and staff about the benefits of AI is essential and should include hands-on applications. Case studies and success stories showcase how other real estate businesses are cutting costs, saving time, improving sustainability, and seeing ROIs after adopting AI technology.

If full-scale adoption is too overwhelming or expensive, gradually implementing AI tools through pilot projects is an excellent alternative. Here, building teams can assess how these integrations work with their existing systems and fit in with their workflows.

It’s also vital to ensure that AI implementation, regardless of scale, aligns with strategic goals so teams can see the benefit and ROI of investing in this solution. That could be in the form of slashing energy costs by a certain percentage every month or boosting occupant comfort by a measurable amount.

To tackle concerns around interoperability, AI developers need to work alongside building management teams to build tools compatible with their existing systems. To avoid expensive upgrades, teams should follow an implementation strategy of retrofitting, not replacing.

They must also consider each building’s unique requirements and how humans interact with technology and machinery on a daily basis. Smart HVAC incidents and failures highlight what can happen if integrations are not customized correctly and the interaction between systems and humans is not adequately accounted for.

Rather than building management teams spending hours navigating complex dashboards and analytical tools, AI is now handling a lot of that heavy lifting, analyzing data in real time and surfacing only the most relevant insights. With AI assistants and autonomous agents, teams can access critical information faster, enabling swift and more informed decision-making. To fully leverage this shift, teams need to ensure that data infrastructures are AI-ready, with clean, interoperable, and well-structured data. Just as importantly, robust cybersecurity measures must be in place to protect sensitive information and maintain stakeholder trust as control becomes more autonomous.

Embracing a future where the built environment is driven by AI requires building owners and managers, stakeholders, and AI developers to work smart, and work together. Through collaboration, we can look forward to a world of smarter buildings that are simple and seamless to manage.