Forget chatbots; AI’s most powerful applications aren’t always flashy, they’re foundational – and a truly smart built environment will be human-centric, writes Gaku Ueda, CEO of Mode
In the near future, technology will be foundational to buildings. The industry is now entering a new phase of innovation for creating smarter and more efficient buildings.
Soon enough, AI’s presence in commercial real estate (CRE) will be a staple: Gartner predicts that 94% of power and utility chief information officers plan to increase their AI investments this year.
Buildings that self-adjust heating and room temperature, dim lights and help navigate maintenance teams depending on real-time information about traffic flows, occupancy and more will be the norm in the new wave of innovation.
AI in the physical world is an exciting area of innovation emerging in the CRE industry. It is extending what AI stacks can do, meaning they can now interact and change their surrounding environment based on real-time information.
Picture an intelligent physical system in a building, where AI picks up on data from sensors and informs the physical system to instantly adjust air conditioning for optimal energy control and enhanced occupant comfort.
The long-term impacts of AI are wide-ranging. Crucially, building managers must also understand best practices for integrating AI to maximise those impacts, including keeping the human presence at its core.
The growing need for smart and integrated monitoring
Traditional digital infrastructures in building management are plagued with disconnected systems that lead to poor oversight, missing information and limited efficiency. Adding separate tools without considering how they operate alongside each other exacerbates data overflows and disconnected systems that are difficult to manage.
Interoperability becomes a bigger challenge given that AI tools process information in real time and are constantly changing at a rapid pace.
That’s why it’s crucial for building operations to have a unified platform, ensuring complete data visibility and keeping a pulse on building status in one place. AI can be integrated alongside this, feeding insights and analysing data to monitor building performance around the clock and prevent any damage. It’s then easier for building managers to leverage AI-generated insights to improve performance or uncover underlying anomalies.
With integrated systems, teams can also pinpoint where greater efficiencies exist. An AI solution informed by sensor data and cameras can flag that a certain floor or room has less footfall than before and indicate when air conditioning can be reduced or switched off. As a result, the building management cuts down its energy bill while ensuring traffic areas are at
a comfortable temperature for occupant satisfaction.
These insights can also help teams predict when maintenance is needed or systems are likely to fail. To illustrate, a firm integrated AI across 165 HVAC chillers alongside three years of sensor data to train a machine learning (ML) model.
The algorithm enabled the firm to predict failures early on, with 73% precision, helping the management team slash system downtime and maintenance costs.
Building the foundation for AI integration
A recent survey by PwC shows that 46% of the CRE industry strongly feel that AI will transform the value chain in the next five years.
An important distinction must be made: while AI solutions in the past worked much like black boxes, those of today, such as generative AI (GenAI), are designed to enhance human capabilities, not replace them. AI isn’t just about helping automate processes; it is also about driving visibility for people to make more effective decisions accordingly.
The first point of call is tackling any data challenges, like siloed or fragmented data. No AI platform or tool will function properly with poor data inputs. The widespread interoperability challenge has caused massive data fragmentation.
Besides that, management teams will never achieve proper AI governance or establish trust among teams if their data is not fit for purpose. Organising and cleaning up data so it is accurately shared across the system is a vital starting point.
Additionally, building managers should adopt tools that can be integrated into existing systems, not simply add a new layer of technology that can lead to interoperability challenges. For example, smart HVAC systems, that can monitor energy consumption and self-adjust accordingly while optimising building performance, are among the most attractive aspects of AI in buildings.
Finally, AI should empower human decision-making to make buildings more comfortable, sustainable and cost-effective. To achieve that hybrid approach, teams must be well-trained in leveraging and overseeing AI. Implementing a management framework with established protocols for AI accountability, overriding issues, human intervention and security is necessary. That way, building managers can ensure these tools are used safely and streamlined.
The buildings of tomorrow will have AI embedded in their foundations. However, human oversight remains a core aspect of successfully using AI to transform buildings into smart hubs. Understanding the blueprint and the frameworks that need implementation guarantees lasting transformation.
The post How human-centric integrated AI is modernising building management appeared first on Planning, Building & Construction Today.
