Artificial Intelligence (AI) Gains Traction In Commercial Buildings

By Neil Strother
From the December 2020 Issue

The hype around artificial intelligence for commercial buildings is starting to ebb. No longer do facilities managers have to merely accept the marketing message and hope for positive outcomes. Now, they can point to actual deployments or use cases where artificial intelligence (AI) is gaining traction. For example, 10 commercial buildings in the U.K. and Ireland are implementing an AI-powered solution¹ from BrainBox AI. These recently announced deployments encompass more than one million square feet of space. The BrainBox AI solution uses AI to predict a building’s thermal load and enables the HVAC system to operate autonomously in real time with greater efficiency. The solution is expected to reduce total energy costs, decrease the buildings’ carbon footprint, and boost occupancy comfort by double-digit percentages.

artificial intelligence (AI)
An important step to AI adoption is to quantify connected assets. Identify how many and what types of HVAC controls, sensors, relays, and communications devices are available and in use.

Madison International Realty offers another example of AI adoption. The private equity real estate firm has partnered with technology vendor Carbon Lighthouse on Madison’s revitalization project at the Atlantic Terminal Mall in New York City. The Carbon Lighthouse CLUES AI platform calculates energy waste across HVAC and lighting systems at the mall and enables the implementation of efficiency measures. By combining the energy savings at the mall with the neighboring Atlantic Center, the effort is expected to eliminate more than 7,000 tons of carbon emissions.

Alphabet-owned Sidewalk Labs has entered the fray as well through launching a solution called Mesa. The AI-powered Mesa solution is aimed at older and smaller commercial buildings with the goal of reducing energy costs by up to 20%. Sidewalk Labs says it has already piloted Mesa² in two undisclosed office buildings in New York City. Also, it plans to expand its efforts with other commercial landlords and tenants ahead of launching products aimed at solving sustainability and affordability challenges. Some caution might be in order, however. In May of 2020, Sidewalk Labs abandoned its controversial efforts to develop a smart neighborhood in Toronto’s Quayside district, citing unprecedented economic uncertainty amid COVID-19 as the reason for the pullout. But the Quayside initiative also faced daunting concerns from high profile advisors and others, who expressed serious doubts about privacy and the handling of personal data.

Artificial Intelligence’s Momentum Keeps Growing

Despite the Sidewalk Labs controversy, the momentum behind AI for commercial buildings keeps growing. And though it might appear to be a new phenomenon, the use of AI goes back at least a few years, well before the pandemic. In 2015, for instance, Spanish banking giant BBVA designed its headquarters in Madrid to be energy efficient at the outset, installing 50,000 sensors to gather data about the status of the facility, environmental conditions, and the presence of people. Facilities managers had an inkling back then that all of the data would be useful for AI solutions, and it has been. BBVA’s headquarters’ facilities managers have developed AI-based software that detects and diagnoses issues that can be corrected to produce even greater efficiencies. They have also employed more than 100 savings measures, enabling the headquarters to reduce energy consumption by 12% to 15% since the facility opened.

Doubts About AI Remain

Even with case studies and past deployments, many building owners and facilities managers have doubts about using AI. Shifting to a new technology like AI brings added costs, and many remain skeptical about the outcomes and uncertain about the ROI. What should alter perceptions in this vein is a growing body of repeatable case studies that show a positive ROI across multiple building types. Many now realize that AI is not some magical digital wand to be waved; instead, it is a useful tool for solving fairly mundane problems.

Key building stakeholders are not technology averse either; rather, they are more practical and methodical. What they could use is a strategy for AI adoption, which starts with the notion that AI is part of a journey toward smarter facilities. At Guidehouse Insights, we recommend several steps along that path:

  • Choose a pain point or problem that an AI tool might be able to solve. Do not take on multiple problems at once; instead, start small and build from there.
  • Quantify connected assets. Knowing how many and what types of HVAC controls, sensors, relays, and communications devices are available and in use becomes the starting point for determining the additional hardware needed to enable an AI solution.
  • Have financial managers and facilities managers do a thorough cost assessment. Moving ahead on an AI project often means spending for a combination of connected Internet of Things-type equipment, software, and services.
  • Deploy an AI-supported project once the above steps have been taken. Then, measure the impact with key ROI metrics. As the process unfolds, make course corrections.

These steps alone cannot guarantee success with artificial intelligence, but they provide a guide for facilities managers as they consider how to harness the promise of AI, knowing there are some pitfalls and uncertainty. Stakeholders should bear in mind that a technology like AI is part of the overall trend toward smarter buildings, and the message is don’t get left behind. AI can drive greater value and positive outcomes from buildings.

For more details on the topic of AI, see Guidehouse Insights’ report³ The Future of AI for Smart Buildings.



artificial intelligence (AI)Strother is a principal research analyst contributing to Guidehouse Insights’[4] Building Automation and Control solution, with a focus on the Internet of Things trend, smart metering technologies, and home energy management solutions. He has an extensive background in market intelligence focused on emerging technologies. Prior to joining Guidehouse Insights, Strother was practice director of mobile services at ABI Research. He previously held senior analyst positions at Forrester, and NPD. He was also the managing editor of ZDNet AnchorDesk. Strother holds an MS from Northwestern University and a BA from Whitman College.

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