Artificial intelligence is becoming increasingly significant in facility management. In particular, predictive maintenance is a significant application of AI in this domain. Predictive maintenance is the process of using data to predict when equipment will fail and needs to be repaired or replaced. This is significant because it can help prevent equipment failures, which can lead to disruptions in service. With the pressure on organizations to do more with less, Facilities Management (FM) must challenge itself to be a strategic business enabler.

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Buildings have been one of the most voracious users of IoT devices. Smart buildings, in particular, use connected devices to measure everything from temperature, lighting, air quality, noise, vibration, occupancy levels and energy consumption -- and that's just the very tip of the iceberg. Building automation is big and getting bigger, with well over 6 million commercial buildings in the U.S. alone and an estimated 2.2 billion connected devices deployed. The global market for building automation systems in 2022 will reach about $80 billion.

Facility management is the part of the business that has always been under pressure to'do more for less' and to deliver the magic 10% cost savings that the core business demands of it. As businesses start the slow road to recovery and begin to emerge from the pandemic and enforced lockdowns, facility management and its associated costs will again be under the microscope. Traditionally, these cost savings have come from market testing, outsourcing, re-tendering, re-scoping, head count reduction and other areas of efficiencies that have by now, challenged the simultaneous demand for improved service quality and performance. Whist technology has played an important part of facility management for some time now, through a hunger for data to measure performance and through BIM and SMART or intelligent buildings, enabling informed decisions to be made, there is now a new opportunity for the use of technology in facility management and this is arguably the biggest opportunity yet. Facility management is involved across every organisation, and markets across both the private and public sectors and in commercial and non-commercial entities.

Artificial intelligence (AI) is a beneficial tool for facilities management (FM) teams, that can save money, reduce energy usage, improve productivity, and more. Thanks to AI technology, various aspects of everyday life have evolved, from how we work at the office to how we order groceries or shop online. The Oxford English Dictionary defines AI as, "the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages." In this article, we're sharing a few ways AI is already impacting FM teams and organizations as a whole for the better. AI is completely changing the way some organizations cut costs on vital areas of operations like energy, HVAC, security, and other systems.

Newly accessible advanced computing techniques like machine learning and artificial intelligence can help.

Buildings are a central part of the world today. We live, work and play in them. We socialize, learn and engage in them. In fact, it's estimated that we spend 93% of our time in buildings. Of course, buildings don't remain static once the builder hands over the keys – their uses, occupants and components vary and change with time.

With artificial intelligence integrated into building systems and IoT devices, buildings become more than their brick-and-mortar shells. They begin to operate in new ways, creating personalized experiences for their occupants, and providing energy and cost savings for their owners. In the report'Building intelligence into buildings', the Institute of Business Value (IBV) explores the potential of buildings that think for themselves. Below are some of the key learnings and action points. What if buildings owners could see exactly how their building is being used at any given time?

The RICS has launched an insight paper which explores the impact of using artificial intelligence (AI) in the built environment, and the urgent need for industry professionals to understand how it will influence their role, as the future will rely less on human labour and more on technology. Authored by Chris Hoar, Brian Atkin and Katie King of AIinFM, the report examines the potential impact of AI on the built environment, with a focus on facilities management. One sector that the Artificial Intelligence: What it means for the built environment highlights as facing a significant impact of AI is facilities management (FM), due to the labour-intensive and repetitive nature of many FM jobs, making it an ideal place for automation of previously human-dominated tasks. However, the report weighs up the positives and negatives of such changes and how companies should deal with them. FM will always have a vital role to play within the built environment, and even though many operational roles will become more technology-led, the sector could benefit hugely from AI at a strategic level.

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Facility management might not sound like the sexiest use of AI technology. But office space can be a huge expense for larger businesses -- the biggest after staff costs -- which is why Y Combinator-backed startup, VergeSense, says it's settled on facility management as the initial target for an AI-powered sensing device it's been developing since joining the incubator program in May. Their "sensor as a system" platform, as they dub it, consists of sensing devices containing a series of different sensor hardware, including an image sensor, coupled with a cloud platform for pre-training machine learning models that run on the hardware, process data and report occupancy analysis back to VergeSense's cloud. "We're using really inexpensive hardware… we've crammed a bunch of different sensors inside. The core of the product is actually built around computer vision, so we've got a really inexpensive image sensor that's embedded inside," VergeSense co-founder Dan Ryan tells TechCrunch.