Focusing on key global cities such as Singapore, Amsterdam, Dubai, Tokyo, London, New York, Melbourne and Buenos Aires, the report provides deep insights into the evolving nature of work, highlighting significant shifts in workplace strategy, technology adoption, and employee expectations.

As to key trends, the report underscores a surge in hybrid working models: although the return to office is gaining momentum, 85% of organizations are now prioritizing flexible work arrangements, which is reshaping business districts.

It also identifies AI-driven automation as a major driver of efficiency, with 72% of companies integrating artificial intelligence (AI) tools to streamline operations; smart mobility and AI-driven solutions are transforming urban life and the infrastructure.

Sustainability remains a key focus, with businesses increasingly investing in eco-friendly office spaces and carbon-neutral policies; cities are prioritizing sustainability, inclusivity, and connectivity to build a better future

As well as identifying these key trends, the report reveals three core categories of cities:

• Innovation-led cities (e.g., Singapore, Amsterdam, Dubai) are rapidly evolving and heavily investing in innovation and people.
• Steadily evolving cities (e.g., Tokyo, London) are leveraging their size and resources for gradual change.
• Adaptive cities (e.g., New York, Melbourne, Buenos Aires) are showing resilience and adapting to pressures.

Commenting on the findings, Philip Ross, CEO of UnGroup (UnWork, WORKTECH and WORKTECH Academy), stated:

Work is undergoing a fundamental transformation. Organizations must embrace innovation, from AI-powered workplaces to dynamic hybrid strategies, to stay competitive. Our report provides a roadmap for leaders navigating this rapidly changing landscape.

By taking a deeper dive into eight world cities, this report aims to show how a greener, smarter, more inclusive and more connected urban future is being built in specific locations and under specific conditions. Businesses that adapt to these trends, and successfully align technology, culture, and sustainability will be best positioned for long-term success.

Wish You Were Here: Eight World Cities Shaping the Future of Work is available to WORKTECH Academy members (others may join today to access it).

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AI in the building maintenance industry leverages machine learning algorithms and data analytics to enhance efficiency, cost-effectiveness, and overall performance of building maintenance processes. Used for predictive maintenance, energy management, and smart building management systems, AI technologies come with a host of benefits.

Recent technologies are able to summarize maintenance schedules for quick reference, highlighting asset types and locations, easing the process for engineers and facility managers. Similarly, AI is capable of analysing asset register data to automatically identify and map appropriate maintenance schedules to each asset — a task that frequently takes months to do manually.

While spotlighting the advantages AI can bring to maintenance professionals, the industry must also be aware of its pitfalls.

What are the pros of using AI technologies in a building maintenance strategy?

1. Cost reduction 

AI can automate the repetitive tasks associated with setting up maintenance plans and ensuring they are optimal and legally compliant. Efficient and effective maintenance relies on a strong understanding of the facilities and assets that require maintenance and an informed plan to address them. AI provides a new capacity to create a deeper understanding that would be unfeasibly costly to implement using human resources.

AI can be used to minimise maintenance costs by decreasing unplanned downtime and optimising energy consumption.

As AI provides real-time data analysis and insights that can help facility managers make more informed operational decisions, this can reduce the likelihood of costly errors in judgment.

2. Time efficiency 

By automating tasks, AI tools can help maintenance professionals work more efficiently by streamlining processes and cutting down on timely repetition.

AI software tools can assist with many traditionally manual tasks, speeding up repetitive processes and helping to standardise data. In the long term, this can save those responsible for building maintenance both time and effort, which can be used in more strategic, high-impact areas.

3. Maximises asset lifespan 

AI-powered solutions can extend asset lifecycles by predicting potential failures before they occur.

By recommending the best timing for maintenance (not applicable for statutory requirements), AI can, in turn, prevent both over-maintenance, which can cause unnecessary wear, and under-maintenance, which can lead to premature failure.

4. Provides more reliable reporting and analytics 

AI in facilities management is incredibly helpful for collecting, analysing, and simplifying the array of information involved with building maintenance and its associated responsibilities, including diagnosing problems.

Machine-learning AI can interpret data from various sources, including sensors and real-time user inputs, to identify patterns and make intelligent, personalised predictions about building management needs, for example, previous patterns of equipment failure.

In the past, data had to be sorted manually, with decisions often being made without clear, evidence-backed reasoning. Now, through machine-learning AI, data reporting and analytics can be achieved faster and more reliably than ever before, lowering the risk of human error.

What are the cons of leveraging these technologies?

1. High initial costs

Despite its benefits, the implementation of AI in building maintenance is not without challenges – the most obvious being the initial cost of deploying AI systems, such as sensor installation and integrating AI solutions. This upgrade can be particularly costly for older buildings.

Implementing AI systems can require significant upfront investment in hardware, software, and training, so careful planning and budgeting are essential for a successful and cost-effective onboarding.

2. Data Privacy and Security Concerns 

As AI systems collect and process large amounts of sensitive building and occupant data, this may cause privacy and cybersecurity concerns for an organisation.

As AI systems require high-quality, consistent data to function effectively, poor or incomplete data can lead to inaccurate insights or decisions.  In other words, AI is only as good as the data that goes into it.

Ensuring this data is collected, stored, and used in compliance with privacy regulations is crucial.

3. Overreliance 

Industry professionals must always approach AI adoption with caution and not fall into a cycle of overreliance. Artificial intelligence tools are not infallible; they require rigorous data validation and continuous human oversight. Facility management systems are complex and demand nuanced interpretation that AI algorithms may not fully comprehend

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In this study of U.S. building managers and decision makers with more than 250 building occupants, Honeywell found that across property types, respondents are increasingly using AI to help improve process efficiency, productivity and operations. However, since most respondents (92%) reported challenges in hiring skilled, tech-savvy individuals, a greater opportunity remains ahead for building operations to tap into AI’s capabilities to enhance employee training, augment their current workforce and ultimately help upskill labor to support the sector’s rapidly changing needs.

Billal Hammoud, president and CEO of Honeywell’s Building Automation segment,  stated:

AI in buildings is a game-changer that not only helps decision makers potentially maximize operations and efficiencies, but it can also help improve security for guests, minimize energy usage for tenants and reduce costly downtime by flagging issues before they happen. With basic AI functions already integrated into many commercial buildings, leaders should pivot their focus to the upskilling opportunities it presents for employees who can tap into AI to help buildings reduce carbon emissions while being more secure and operationally efficient.

For commercial buildings, Honeywell’s research found that AI has moved beyond experimental and is now becoming mainstream, as evidenced by its increased usage for day-to-day building management. Key findings include:

• Nearly 60% of respondents have already adopted AI to streamline maintenance and repair processes.
  • One of the most common use cases is predictive maintenance, which helps identify issues before they become larger concerns and is currently used by 49% of respondents.
• Security and safety are also top-of-mind for more than half of all respondents.
  • Frequent use cases cited by respondents were monitoring for unusual behavior (63%), location tracking systems for occupant safety (52%) and biometrics-based access control systems (45%).
• Decision makers are turning to AI for everything from temperature control to water usage.
  • More than half (55%) of respondents currently use AI for overall building energy management, 41% use it for water usage monitoring, and 40% implement it for temperature comfort.

To learn more about the AI in Buildings research results and how Honeywell’s solutions are helping buildings deliver stronger operational efficiency and fire and life safety, visit Honeywell’s Building Automation division.

Honeywell commissioned Wakefield Research to conduct the Honeywell Building Managers Research Survey, which polled 250 U.S. building managers and senior decision makers across building types including offices, hospitals, airports, schools, universities, hotels and data centers. To participate in the research, respondents had to use AI-enabled property management systems in buildings with 250+ occupants.

Honeywell is an integrated operating company serving a broad range of industries and geographies around the world. Its business is aligned with three megatrends — automation, the future of aviation and energy transition — underpinned by the Honeywell Accelerator operating system and Honeywell Forge IoT platform. The company helps organizations solve complex challenges, providing actionable solutions and innovations through its Aerospace Technologies, Industrial Automation, Building Automation and Energy and Sustainability Solutions business segments to increase safety, security and sustainability.

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By Sara Marberry  — I’ve been having a lot of conversations with people about AI recently. Love it or hate it, AI is here to stay and will only grow in importance in our daily lives.

AI isn’t perfect.

It sometimes messes things up. Its ability to generate highly realistic deepfake videos and images is very disturbing. And some think AI could surpass human intelligence and take over the world.

But AI isn’t inherently good or evil — it’s all about how we use it.

AI in healthcare

In healthcare, AI is already impacting patient care, staff productivity, and facility design.

AI-powered imaging tools can detect anomalies like cancer, fractures, or infections faster and with higher accuracy than traditional methods. It also scrutinizes patient data, genetics, and past medical history to tailor treatments specific to individual needs.

And there’s more.

AI models can analyze trends and identify individuals at risk of diseases like heart disease or diabetes before symptoms appear, enabling early interventions. AI-powered virtual assistants and chatbots are able to provide 24/7 patient support, answer medical queries, schedule appointments, and even help monitor chronic conditions remotely.

By reducing administrative burdens and optimizing workflows, AI is also reducing time spent on things like paperwork and data entry, allowing staff to focus more on patient care.

AI in healthcare facility planning and design

A recent paper published by the American College of Healthcare Architects offers a great overview of AI in healthcare facility planning and design, with 10 conclusions and predictions at the end. Some that stood out for me are:

1. Data-driven design: AI’s ability to collect data in a number of different areas. such as outpatient care and customer preferences, will inform new and flexible facility design solutions.
2. Efficiency and workflow optimization: By streamlining administrative tasks, AI will free up time for healthcare professionals and eliminate the need for some staff. This will impact the types and amount of workspaces that are needed.
3. Population data mining for everyone: AI’s ability to analyze and predict diseases and new treatment options will present new design challenges

On the creative side, AI allows healthcare architects and designers to run different scenarios for their designs by generating multiple solutions based on specific things like space utilization, sustainability, and aesthetics. It’s also being used to design more energy-efficient buildings by simulating how they will interact with natural elements such as sunlight, wind, and temperature.

AI-powered virtual staging tools can give clients an idea of what a space might look like with out physical staging. And AI can be used to suggest furniture arrangements, color schemes, and design themes.

What to make of AI

So, are all of you healthcare architects and designers going to be replaced by AI? Heck no. It cannot replace the deeply human qualities of empathy, ethics, intuition, and a sense of purpose that is essential to you and the work you do.

But if you’re not using AI as a tool to help problem-solve, stimulate your creativity, and produce better designs, then you’re missing the boat.

See the original article as well as more insights on Sara Marberry’s Blog.

This column originally ran on Sara Marberry’s Blog on February 28, 2025. Marberry is a healthcare design expert with over 25 years of experience in the healthcare and senior living design industry, who has written/edited five books and is a regular contributor to Healthcare Design magazine. Marberry also is a former Executive Vice President of the nonprofit Center for Health Design.

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As the market matures and barriers to adoption fall, a diverse range of vendors are vying for market share. From established building technology providers to a new wave of agile start-ups, firms are leveraging cutting-edge technologies to offer solutions that address the evolving needs of building owners and operators and solidify their market position.

The benchmark Verdantix Green Quadrant: IoT Digital Platforms For Building Operations 2024 report provides property owners, asset managers, real estate executives and facilities managers with comprehensive insights into 12 prominent IoT digital building platforms, helping them select the best-fit provider for their needs. The report identifies four firms — Honeywell, Johnson Controls, KODE Labs and Siemens — as offering some of the most comprehensive services in the market. However, they face growing competition from innovative IoT start-ups, which are striving to deliver the solutions needed to achieve smarter, more sustainable, autonomous building management.

Key report findings:

• Buyers are prioritizing flexible digital platforms that integrate building data, automate operations and enable advanced analytics. While established players such as Johnson Controls and Siemens bring global reach and industry expertise, start-ups such as KMC Controls and KODE Labs offer cost-effective, artificial intelligence (AI)-powered solutions, supporting enterprises and smaller properties alike.
• AI is rapidly transforming building management. Increasingly intelligent platforms are enabling autonomous actions that streamline operations, boost asset performance and enhance occupant comfort. Honeywell, for example, has introduced an AI-powered chatbot to accelerate access to critical data and insights.
• Vendors are adapting their offerings to align with key market trends such as energy optimization and sustainability, offering solutions that drive operational excellence. Many platforms that began as smart building solutions are now marketed as tools for energy optimization, such as Nantum AI.
• Providers in this space offer a range of services, from design and implementation to ongoing support, acting as a trusted partner in the digital transformation journey. For example, e-Magic leverages its TwinWorX platform to tailor solutions.

Claire Stephens, research director at Verdantix, summarized:

In today’s competitive real estate landscape, asset and facilities managers must embrace digital transformation or risk becoming obsolete. As experienced staff retire and technology advances, a tech-driven approach is essential to streamline operations, increase revenue and enhance tenant experience, ensuring that buildings remain competitive. As the market continues to evolve, vendors are racing to provide innovative solutions that empower facilities managers and drive towards a future of autonomous buildings. However, the ultimate winners will be those who can deliver real value and adapt to the changing needs of the industry.

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Large organizations might view AI as an expansive solution aimed at integrating all operational tools or analyzing massive data sets. This approach doesn’t necessarily serve the needs of frontline technicians. Unlike high-level integrations intended for C-suite efficiency and analytics, facility management must prioritize actionable, immediate solutions that directly affect the people on the ground — the technicians.

For many in FM, particularly technicians, there is a notable hesitation around AI, not out of fear, but because most AI applications aren’t relevant to their day-to-day tasks. Technicians spend their time fixing equipment, diagnosing issues, and maintaining systems. Their days aren’t filled with data analysis or report generation, so they don’t require tools that promise enterprise-level insights. Instead, to be beneficial, AI for technicians needs to focus on practical, intuitive applications that can improve workflow efficiency and reduce downtime without requiring significant training or time investment.

Understanding technicians’ relationship with AI

Most technicians in FM are not technology enthusiasts. They’re not likely to spend their weekends exploring ChatGPT, Dall-e, or Gemini, or diving into tech blogs for fun — they’re busy solving hands-on problems. For many techs, their approach to AI is simple: if it can help do their job faster, it’s worth considering. In this respect, AI adoption in FM doesn’t need to focus on replacing tasks but rather, on assisting them.

Ryan Koppelman, VP of Technology, eCIFM Solutions, Inc. explained at IFMA World Workplace:

Generative AI can revolutionize how designs, layouts, and workflows are developed and optimized. Facility managers and designers can leverage generative AI to explore multiple design possibilities and select the most efficient and cost-effective solutions.

Organizations and individuals that commit the time and resources to lean into this technology can benefit greatly. Where many will see the greatest impact will be in what might be considered stealth AI. Software developers are using these new generative AI capabilities to subtly improve the tools we already use.

While AI isn’t likely to perform physical maintenance tasks any time soon — like fixing a rooftop air handler or replacing the fluids on a generator — there are several ways it can empower technicians:

1. Instant access to knowledge: Imagine walking up to a piece of equipment and, without needing to input any queries, instantly having the system provide troubleshooting tips, parts schematics, or installation and warranty information. This capability is a major value-add AI can bring to FM, allowing technicians to access what they need without extensive searches.
2. Predictive suggestions: Like personal devices that suggest frequently visited places when you get in the car, AI can anticipate technicians’ needs. Suppose a technician often checks certain metrics or performs specific tasks for a particular piece of equipment. AI can recognize this pattern and prompt those tasks, reducing the mental load and time spent finding information.
3. Simplified mobile solutions: Today, most technicians carry smartphones. The challenge has been that many FM tools are too complex or weren’t designed with mobile use in mind, making them cumbersome for technicians to use them on the job. AI can streamline mobile apps to intuitively prompt the information needed, making it easy for technicians to complete tasks without being hindered by technology.

Shifting focus: AI tools that do the heavy lifting

For technicians, the goal isn’t to learn complex AI algorithms or to understand AI at a granular level. Instead, FM professionals benefit most from tools that “do the thinking” for them. AI can be integrated seamlessly, removing the need for technicians to learn coding, complex prompting, or system integration. It should simply work as an “assistant,” helping technicians find solutions on the fly without requiring deep interaction or customization.

Like Amazon’s intuitive product reminders: the system knows when certain supplies or parts may be needed and can proactively suggest restocking. This approach, which leverages AI to anticipate needs, can empower technicians to stay ahead without added complexity.

Mobile-first, technician-centric solutions

While tablets are becoming more common, phones are still the go-to tool for most technicians. Many FM tools are still based on legacy designs with desktop use in mind and are not optimized for mobile. This lack of mobile functionality has been a barrier to FM AI adoption. To truly empower technicians, the industry must prioritize mobile-friendly, AI-enhanced solutions that are efficient and easy to use.

AI-powered mobile tools tailored to technicians could streamline workflows by making essential information accessible anytime, anywhere. When entering an equipment status update, a mobile AI tool could prompt the technician with the most relevant fields or possible actions, such as suggesting preventive maintenance tasks based on recent activity. This user-focused AI delivers technicians the information they need without unnecessary steps.

Balancing industry trends and technician realities

While it’s tempting to think of AI as a panacea for FM challenges, it’s essential to differentiate between high-level tech integrations suited for large-scale companies and the actionable tools that frontline technicians need. AI’s effectiveness in FM will depend not on just the needs of accounting teams or executives, but also on how well it optimizes workflows, reduces the burden of manual data entry, and supports technicians with accessible, mobile-first tools that bring intelligence directly to the field.

While organizations are busy implementing large scale AI tools for analysis and to improve decision-making, it is important to also remember empowering technicians with thoughtful, focused AI applications that save time, reduce errors, and improve safety by delivering critical information at the right moment.

About the Author

Jonathan Styrlund is a vice president at ARC Facilities. Styrlund joined ARC in 2001 and has managed the development of several of the company’s technology products. Today, he oversees development of the award-winning ARC Facilities solution, which uses AI and machine learning to allow facilities professionals to instantly access critical building information from any mobile device.

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AI servers, driven by Nvidia’s GB200 superchip, have experienced significant growth. The cutting-edge B200 chip, due to its high thermal design power, requires direct-to-chip cooling. Supermicro announced that it had shipped over 2000 direct-liquid-cooled AI server racks by the end of August 2024, and it has expanded its manufacturing capacity to 5000 racks per month. Supermicro reported that it has around 75% of the liquid-cooled AI server rack market, and IDTechEx believes that this production capacity expansion will lead to a surge in liquid-cooled server racks, as well as the number of cold plates. The projections for the number of cold plates for AI servers in IDTechEx’s new report, “Thermal Management for Data Centers 2025-2035: Technologies, Markets, and Opportunities”, align with Supermicro’s latest announcement.

IDTechEx believes that this production capacity expansion is expected to drive a rapid increase in the deployment of liquid-cooled racks across the AI and high-performance computing (HPC) sectors, along with a notable rise in the use of cold plates. Cold plates are integral to direct-liquid-cooling systems, as they are responsible for absorbing and dissipating the significant heat generated by high-performance chips like Nvidia’s B200. IDTechEx’s recent research into thermal management for data centers echoes Supermicro’s projections, highlighting the increasing importance of liquid cooling technologies in managing the heat loads associated with next-generation AI and HPC hardware.

Direct-to-chip (D2C) cooling, also known as cold plate cooling, is a sophisticated cooling method wherein a cold plate is mounted directly onto the chip (GPU or CPU). The plate facilitates the transfer of heat from the chip to a circulating coolant, which then dissipates the heat. D2C cooling can be divided into two main categories: single-phase and two-phase systems, depending on the type of coolant used. Single-phase D2C typically uses a water-glycol mixture, which circulates through the system and transfers heat away from the chip via convection. This type of cooling is efficient for systems with moderate TDPs, as the coolant remains in a liquid state throughout the process. In contrast, two-phase D2C cooling uses a coolant like fluorinated refrigerant, which absorbs heat through a phase change. As the coolant transitions from liquid to gas, it provides significantly greater cooling power, making it well-suited for systems with extremely high TDPs.

The rapid increase in chip TDPs is driving the demand for more advanced cooling solutions. AI and HPC applications, in particular, are pushing the limits of current cooling technologies, as these workloads require chips with significantly higher power consumption to handle complex computations. Nvidia’s GPU roadmap, combined with Intel’s recent announcement of its Falcon Shores GPU — expected to have a TDP of 1,500W — suggests that GPUs and CPUs with TDPs exceeding 1,500W likely become common within the next one to two years. IDTechEx predicts that this ongoing rise in TDP will eventually lead to a shift from single-phase to two-phase D2C cooling systems, as the latter offers superior heat dissipation capabilities required for these high-power chips despite the unclear timeline.

In addition to direct-to-chip cooling, immersion cooling has garnered significant attention as an alternative solution for high-performance systems. Similar to D2C, immersion cooling can be split into two categories: single-phase immersion cooling (1-PIC) and two-phase immersion cooling (2-PIC). However, unlike D2C, immersion cooling involves submerging the entire server into a bath of coolant, which absorbs heat directly from all components. This method is highly effective for cooling densely packed systems with high power requirements, as it eliminates the need for air-based cooling entirely. In single-phase immersion cooling, the coolant remains in a liquid state, similar to single-phase D2C. Two-phase immersion, however, leverages a phase change in the coolant, similar to two-phase D2C, to provide even more efficient heat dissipation.

While immersion cooling offers numerous advantages in terms of thermal efficiency, it comes with several challenges. The process of submerging servers requires extensive retrofitting of existing infrastructure, as well as rigorous material compatibility tests to ensure that the components can withstand prolonged exposure to the coolant. This results in higher upfront costs compared to D2C cooling systems. Additionally, immersion cooling systems, especially two-phase variants, face regulatory challenges. For example, 3M’s Novec products, commonly used as two-phase coolants, are set to be discontinued by the end of 2025. As of now, no PFAS-free or “forever chemical”-free two-phase coolants have been officially announced, adding another layer of complexity for companies considering immersion cooling solutions.

Cooling in data centers occurs at various levels, ranging from chip-level to facility-level cooling. Each level requires different cooling strategies, with technologies like D2C and immersion cooling primarily focusing on chip, server, and rack-level thermal management. At the room and facility levels, air-based cooling remains the most common approach in 2024. Computer room air conditioning (CRAC) units and computer room air handling (CRAH) units are widely used to cool entire server rooms or data center floors. However, the growing heat loads generated by high-performance AI and HPC systems are pushing the limits of air cooling, prompting the adoption of more efficient liquid-based solutions.

One such solution is liquid-to-liquid (L2L) cooling, which is becoming increasingly popular for facility-level heat management. In L2L cooling, a cooling distribution unit (CDU) transfers heat from one liquid loop to another, enhancing heat exchange efficiency. This system is particularly effective for data centers dealing with higher heat loads from AI and HPC workloads. Supermicro’s CEO has predicted that liquid-cooled data centers, which currently represent around 1% of the market, will grow to 30% by 2026. IDTechEx shares this optimistic outlook, noting that while L2L cooling is gaining traction, its widespread adoption will likely be concentrated in newly constructed data centers due to the significant retrofitting required for existing facilities. However, many existing data centers, particularly those using CRAH units, already have facility water systems in place, which can be leveraged for L2L cooling retrofits. These existing water systems are often the starting point for upgrading older data centers to accommodate more advanced liquid cooling technologies.

In conclusion, the rapid rise of AI and HPC applications is driving a fundamental shift in data center cooling strategies. As chips like Nvidia’s B200 and Intel’s Falcon Shores GPU push the limits of thermal design power, direct-to-chip and immersion cooling solutions are becoming critical to managing the heat loads in modern data centers. This unprecedented transition brings significant opportunities to players in the data center cooling value chain, including but not limited to coolant suppliers, server makers, system integrators, cold plate manufacturers, materials suppliers, and cooling equipment (e.g., HVAC) suppliers. More details about the opportunities can be found in the research report.

To learn more about the report, Thermal Management for Data Centers 2025-2035: Technologies, Markets, and Opportunities, including downloadable sample pages, visit IDTechEx.

For the full portfolio of thermal management market research available from IDTechEx, visit IDTechEx Thermal.

Upcoming free-to-attend webinar

Data Center Liquid Cooling — 6-Fold Market Size Expansion in 10 Years

Yulin Wang, senior technology analyst at IDTechEx and author of this article, will be presenting a free-to-attend webinar on the topic on Wednesday 30 October 2024 – Data Center Liquid Cooling – 6-Fold Market Size Expansion in 10 Years.

The webinar will include:

• Air cooling overview
• Direct-to-chip cooling: An exploration of technical barriers and advantages of single- and two-phase D2C cooling
• Immersion cooling: An examination of single-phase and two-phase immersion and their technical and commercial barriers.
• Coolant comparison and regulations: A comparative analysis of coolants used in liquid cooling systems, including costs, regulatory requirements and operating temperature
• Data center cooling value chain and liquid cooling on the data center facility level
• Cost analysis of data center cooling
• Thermal interface materials: An overview of the critical TIMs in efficient heat transfer within cooling systems
• Market size forecast and future opportunities

IDTechEx will be holding exactly the same webinar three times in one day. Click here to register for the session most convenient for you. If you are unable to make the date, IDTechEx says to register anyway to receive the links to the on-demand recording (available for a limited time) and webinar slides as soon as they are available.

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Dean Stanberry, past chair of IFMA’s Global Board of Directors and a member of IFMA’s AI in FM Working Group, stated:

With AI dominating much of today’s technological discussions, FMs must learn to harness its capabilities and applications. This guide serves as both a roadmap and a compass for facility managers. It offers step-by-step guidance on starting, scaling and sustaining AI initiatives. The insights shared are drawn from industry research, expert opinions and practical experiences, making it a valuable companion for any FM looking to stay ahead of the curve.

In Gamechanger, readers will discover clear and practical explanations of key AI concepts such as machine learning and machine vision. More importantly, they will gain valuable insights into how these technologies can effectively apply to real-world FM challenges. The guide provides a step-by-step approach to successful AI deployment, offering actionable advice on aligning AI strategies with business goals, managing organizational change, and ensuring data governance and infrastructure readiness. Crafted with the busy facility manager in mind, the guide is designed to be accessible, making AI a practical and achievable asset for any FM professional.

IFMA Global Chair Lynn Baez remarked:

AI in FM brings many questions from the C-suite to rank-and-file employees, and rightly so.  Gamechanger equips FMs to take the lead in answering those questions and turning those inherent challenges into opportunities to prepare their organizations and people to succeed.

As the future of facility management continues to evolve, Gamechanger empowers FM professionals to stay ahead of the curve, harnessing the power of AI to improve efficiency, reduce costs and elevate the occupant experience. This publication is a valuable resource that instills confidence in anyone looking to build a successful partnership with AI and lead the way in the next generation of facility management.

Gamechanger: A Facility Manager’s Guide to Building a Relationship with AI is available to IFMA members to download via IFMA’s Knowledge Library.

Panel discussion October 10 at WW

The publication will be a part of a panel discussion titled Harnessing AI for the Future of Facilities Management, featuring working group members who contributed to the publication.

The discussion is scheduled for October 10 at 3:15 p.m. at IFMA’s World Workplace 2024 Conference and Expo in San Antonio, Texas, USA, at the Henry B. Gonzalez Convention Center.

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Skilled trade workers have mixed feelings about AI adoption within the industry

Currently, 25% of respondents believe AI should be used to help skilled trade workers streamline tasks during ongoing labor shortages. In fact, 19% of respondents indicated that either themselves or their organizations have begun experimenting with AI-powered solutions to simplify menial tasks. Additionally, one-third (31%) of respondents believe AI can spur industry growth by making the trades more attractive to a younger generation of workers.

On the other hand, nearly one-half (47%) of respondents revealed they are not currently leveraging AI in their day-to-day work and are skeptical of it. Additionally, only 8% of respondents believe AI implementation won’t benefit the fire and life safe industry at all.

Respondents also cited utilizing AI to act as a “personal assistant” to field workers for hyper-personalized and on-the-go learning (13%); streamline manual processes to save time (12%); and enhance learning and development initiatives, such as those delivered via virtual reality (8%).

The utilization of digital tools is positively impacting training and development programs

A full 82% of respondents use digital tools daily to help streamline training and development programs. The majority of respondents within this group recognize the diverse benefits that digital tools offer the skilled trades industry, including:

•     Making training easier (98%)
•     Saving time while training (94%)
•     Streamlining the process of conducting trainings (95%)

However, respondents also noted challenges in leveraging digital tools within their day-to-day operations, despite an increase in the number of participants using five or more tools on a daily basis compared to the 2023 C&E Survey results. For example, 69% of respondents cited collaboration as top challenge for 2024, a significant increase from last year’s results (29%). The top-reported challenges teams face in leveraging digital tools include:

•     Collaboration (69%)
•     Inspection (51%)
•     Complexity of projects (46%)

The majority of industry professionals participate in NFPA training and development programs

Fully 85% of respondents participate in at least one NFPA training and development program a year, and 18% of respondents participate in or offer training or programs twice a year. The top NFPA products and solutions leveraged by skilled trade professionals include:

•     NFPA print publications (66%)
•     NFPA membership (61%)
•     NFPA LiNK (51%)

Challenges persist when it comes to advancing training and development programs, with a majority of respondents (70%) citing lack of time as the biggest barrier. Additional barriers include:

•     Determining the right training (41%)
•     Lack of access to qualified instructors (48%)
•     Overwhelmed with options and/or a lack of time to vet training programs (32%)
•     Keeping track of which trainings are needed to maintain professional licenses (22%)
•     Lack of technology to disseminate trainings to employee bases (18%)
•     Inability to track and/or document training completions by employees (15%)
•     Other (10%)

According to the survey, 19% of respondents noted the skilled labor gap has led to less time for career advancement opportunities through training and certifications. More than one-third (38%) of respondents reported the skilled labor gap has negatively impacted the amount of time and money spent on recruitment and retention, with 14% of respondents turning down projects due to a lack of qualified labor.

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Establishing an enterprise-wide BAS solution streamlines software and hardware solutions across its inventory for all new BAS installations and major modernizations of existing BAS.  A standardized approach will also streamline operations and maintenance contract support, and minimize training requirements by reducing the number of different systems across the portfolio.

In support of this effort, GSA issued a Class Brand Name Justification for the Niagara Framework manufactured by Tridium. GSA’s market research indicates that this enterprise solution is sold and serviced by nearly every major BAS manufacturer, as well as BAS service providers and vendors of all sizes. Both large BAS manufacturers and small business integrators can compete based on this enterprise standard. GSA also anticipates this enterprise-wide solution will help mitigate unnecessary labor and costs resulting from the remediation of disparate systems.

This enterprise BAS solution aligns to GSA’s mission to deliver the best customer experience and value in real estate, acquisition, and technology services to the government and American people.

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