Mark Bouldin, smart buildings and clean air expert at Johnson Controls looks at the role of AI in smart buildings.

AI is the word on everyone’s lips. It’s never been more accessible to the public as the popularity of free generative AI technologies continues to soar. At the same time, simple AI integrations within the programmes that we use in day-to-day life have become the new normal. And when we integrate this technology across the built environment, the opportunity for evolution and expansion is huge.

Thanks to AI and automation, businesses can use a variety of optimisation software to automatically improve cooling, heating, and power generation, as well as to predict and directly monitor workplace energy costs. Facility managers can monitor building performance, improve tenant experience, and achieve sustainability goals by using AI-powered data analytics. Building managers might still believe that implementing such innovative, energy-saving technologies would be a time-consuming, expensive process. But in reality, they are easily and quickly installed in buildings, allowing managers to see results and returns right away.

Step 1: Painting a picture

The first step involves data gathering and analysis. We delve into how FMs can harness IoT sensors and AI-powered platforms to collect real-time data on energy consumption and facility operations. By utilising predictive analytics, FMs can pinpoint areas of energy waste and emissions hotspots, enabling informed decision-making to reduce their carbon footprint. These AI platforms provide managers with a simulated birds-eye view of buildings and assist in decision-making that results in stronger sustainability practices. In addition to energy consumption and waste, AI platforms give managers the ability to monitor asset, space, health, and occupant comfort parameters, all to attempt to increase Environmental, Social, and Governance (ESG) scores. They continuously inspect workplaces, identifying inefficiencies, flagging equipment issues, and recommending the corrective action required to fix them.

Step 2: Accessing real-time insights

Explore how FMs can use AI algorithms to dynamically manage energy usage. Smart HVAC and filtration systems, guided by AI, adapt in real-time to occupancy patterns, ensuring energy efficiency and occupant comfort. Real-world case studies illustrate the significant reductions in energy consumption achievable through AI-driven energy optimisation.

Many platforms even provide an ecosystem of cloud-based apps that let managers and tenants instantly change the temperature, water supply, HVAC systems, and lighting in various parts of a building. Managers can now track real-time spending, gain efficiency insights, and progress directly from their smartphone, making it easier to regularly update stakeholders on sustainability results. Therefore, they are not just gathering data - they can also share it.

Smart, interconnected management platforms have already been installed in thousands of buildings worldwide. By monitoring and enhancing energy efficiency, tenant satisfaction, asset performance, maintenance operations, and space performance, these enterprise management tools are used to improve the comfort of all occupants in any building.

As for sustainability, businesses must look to technology for a vastly improved way of managing utilities and reducing emissions, as costs continue to rise and government regulations change. Without AI innovation, leaders will never be able to affect the same level of meaningful change for themselves, the environment, or our health.

Step 3: Learn, Evolve, Adapt

FMs are encouraged to regularly update AI models to refine emissions reduction strategies. Learning from both successes and failures, FMs can fine-tune their approaches and find innovative new ways to improve. This article emphasises the importance of staying informed about emerging AI technologies, such as generative AI, and how this links with sustainability and ongoing emissions reduction.

When building and company data are interconnected in the cloud, facilities managers can gain a birds-eye view of operations and analyse a building’s data holistically, rather than in siloes. Every business will have unique goals and can focus their analysis accordingly, gaining insights on a number of different areas from energy efficiency to sustainable development to cost-savings. Once potential opportunities for optimisation are identified, managers can ensure adjustments are made autonomously by leveraging the correct AI integrations and smart technologies in each scenario.

When integrated building data is combined with technologies such as Artificial Intelligence (AI) and Machine Learning (ML), we can truly unlock the potential offered by green technologies. Not only will this increase the wellbeing of building occupants, but it will also lead to significant savings in costs and drive businesses closer towards their all-important net zero targets.