Editor’s note: FM Perspectives are industry op-eds. The views expressed are the authors’ and do not necessarily reflect those of Facilities Management Advisor.
As climate risk grows, so does the urgency around sustainability. 2023 was a year of record-breaking climate events, from sustained warming above 1.5°C to billion-dollar climate loss events. It was also a year marked by a surge in regulatory activity, as California passed the Climate Accountability Package in September 2023 and the U.S. Securities and Exchange Commission made its long-awaited ruling on climate disclosures. Property owners and managers in several cities also faced new local mandates.
Yet, when it comes to meeting sustainability targets, commercial real estate (CRE) owners and their operating teams are quickly met with a stark reality: Pursuing environmental, social, and governance (ESG) targets, quantifying their impact, and documenting these efforts is very, very difficult. This is plainly visible in the GRESB 2023 real estate assessment results. Although 62% of participating office entities in the Americas have established net-zero policies, only half of them have made their net-zero commitments public—demonstrating the gap between ESG vision and execution.
While artificial intelligence (AI) has only recently captured our collective imagination, it comes at a fortuitous time. CRE owners and their operating teams have access to mountains of both proprietary and third-party data about their properties. This information can be harnessed by AI and machine learning solutions to bridge the gap between intent and action.
This article explores AI’s potential to support energy management and provides examples of use cases. It also details three actions real estate companies can take to realize the full value of AI and to make meaningful progress against their ESG goals.
How Predictive AI Can Make Real Estate More Sustainable
Many real estate organizations have high levels of maturity in their development of ESG policies and procedures, yet they are in the nascent stage of deployment. As they investigate and launch new energy efficiency initiatives, they’re looking for flexible tools that drive best practices, help them align teams, and deliver accurate, usable data. Here are three examples of how organizations can apply AI to specific real estate goals:
1. Empowering Operational Excellence
Today, operational excellence lies in the hands of individual building engineers. Firms rely on their inquisitiveness, innate drive, and deep commitment to attaining better results in their building to improve energy efficiency. It’s not enough. We need to empower these teams—who have their hands on the steering wheel—with AI-driven analytics and granular energy recommendations. AI can help them make sense of the vast streams of data from the building management system (BMS), meters, and billing records as well as data flows around occupancy and hyperlocal weather. What happens when we empower teams? Some building teams might be able to delay their start time by a couple hours every day—significantly reducing their energy waste and runtime.
2. Aligning Stakeholders
As organizations work to meet their ESG goals, the immense complexity of the CRE operating environment is a significant barrier. Siloed teams and data streams make it hard to cascade goals and accountability throughout the organization, let alone measure the impact of change. AI tools can act as a single source of truth, aligning objectives, finances, resources, and execution responsibilities. They can also function as a translation interface, articulating objectives in a language that resonates with the user—whether it’s kilowatt-hours for one team, carbon emissions for another, or cost savings for yet another.
3. Delivering Data for Decision-Making
Today, energy efficiency decisions are often made based on intuition, sporadic project analysis (such as examining the impact of a single new chiller), or limited, stale data pulled from 45-day-old utility bills. Lacking a broad and consistent data foundation, it becomes a challenge to compare and predict the outcomes of energy projects. AI has the capability to enhance and simplify data collection, transforming it into actionable insights that empower decision-making in real time.
Actions Real Estate Can Take to Realize the Full Value of AI
The potential of AI is enormous, yet CRE industry players must go beyond mere adoption to reap the full benefits. Organizations need to equip their teams, intensify their data-driven strategies, and extract actionable intelligence to seize the moment.
- Take Your Team Along for the Ride: The core of real estate lies in its people, and they’ll continue to play a crucial role in achieving success. Pairing people with technologies like artificial intelligence and machine learning, allows for quick, educated operational decisions. But seeking feedback from teams and providing training on how to effectively use these technologies is critical to realizing the value.
- Adopt a Laser Focus on Predictive Data: Despite the thousands of data points commercial office buildings amass daily, a staggering 90% of this information goes unrecorded. Quality data is the linchpin for performance enhancements. Focus on technologies capable of capturing the building’s proprietary data—sensors, BMS data, utility bills, and more—as well as external factors, such as weather and occupancy, which influence its operations. Centralized access to detailed data allows for the proactive stance needed to achieve decarbonization objectives.
- Select Digital Tools that Spur Action—Not Just Insight: Building management systems, for example, may offer a data lake, but it likely requires additional intelligence layered on top to provide insight into energy consumption patterns, analyze data to maximize efficiency, and generate meaningful, real-time recommendations that the building engineering team can act on. Providing teams with access to the data in the moment they need it, on the device they have in their hand, is foundational for meaningful building-level change.
Conclusion
AI presents a compelling solution for CRE owners and managers, enabling them to address the intricacies of ESG reporting and disclosure requirements, while also elevating their ESG performance. By harnessing AI strategically, buildings can be optimized for sustainability, environmental impacts can be reduced, and governance practices can be fortified. With federal decarbonization goals set for the built environment, including a 65% cut in GHG emissions by 2035 and a 90% reduction by 2050, it’s a critical moment for CRE teams to come together and reimagine their operations.
Lisa Rockefeller is chief revenue officer at Cortex Sustainability Intelligence, an energy insights platform tailored for commercial real estate that operates in more than 45 million square feet of Class A & B office assets.