It’s not a question whether the artificial intelligence revolution will continue. It’s a matter of how AI trends will shape the future of the infrastructure industry. With it comes many questions about job security, data security and how to capitalize on this emerging technology while protecting your business interests.

Roads & Bridges’ panel, Getting Ready for AI: A Panel Discussion with Engineering and Technology Leaders, recently brought together experts from consulting engineering firms and software vendors to discuss the topic.

In the panel moderated by Jalpesh Patel, then business development manager of infrastructure for ALLPLAN (he now serves as Industry Development Manager – Infrastructure at Bluebeam), three experts explored the most pressing questions about AI in infrastructure and how they see it shaping the industry’s future.

Defining AI

Before diving into how AI will transform the infrastructure industry, Patel asked the panelists to define AI.

“AI, in a general sense, is about developing software or machines that have something that appears to be human-like intelligence or can do things that humans would typically be required to do in the software space,” said Terry Walters, the digital delivery evangelist at Maldelo and founder and chief architect at RoadCADdie.ai. “Essentially, it means making software that can learn in some fashion and then use that learning to solve new problems.”

While AI feels brand-new, its beginnings date to the 1950s, when several developers built applications that could learn how to play checkers, Walters explained. From the 1960s to the 2000s, AI’s growth was steady and flat until increasing in the 2010s until today, when it has become a part of most people’s lives.

“AI represents a new toolset and a new capability,” said Don Jacob, the chief innovation officer at Bluebeam. “We’ve recognized the application of the tool is important, but we are focusing on how we help people get projects done better, get the world built better, sustainably in cost and under schedule.”

Eduardo Lazzarotto, the chief product and strategy officer at ALLPLAN, sees AI as a co-pilot to assist and automate what people are doing—not replace them.

“One of the first questions that users and the industry in general have to ask themselves is how do they see the future of AI?” he said. “And what do they want that solution to deliver within their current workforce?”

Prioritizing security and teamwork

According to Walters, the explosion and proliferation of AI tools, especially free tools, are driving companies to shift the allocation of resources and capital.

“People are becoming more efficient because they’ve started to adopt these tools,” Walters said. “They’re either able to get more done or focus on the things that AI still isn’t good at. The important thing though is the security piece, especially when folks are going out to publicly available tools and [inputting] privately contained information.”

Experimenting with AI is the first step, but Jacob said the critical next step is “explainable AI,” which are tools and methods designed to help people understand the results of machine learning. Specifically, these tools are going to be essential with what Jacob calls mission-critical scenarios where human life is at stake.

“Being able to understand why the machine gave you the answer is going to be something very important for us,” he said.

Lazzarotto added that getting to this point is going to require teamwork and collaboration.

“We are always trying to integrate with other solutions to make sure the client has the workflow that they feel is right,” he said. “We’re not trying to force them into a certain aspect of using technology.”

Using AI in the AEC industry

When Walters worked on a recent Texas Department of Transportation project, he generated a “frequently asked questions” document with AI because he had a large amount of data from numerous stakeholders. AIenabled him to condense columns of information from a spreadsheet in 20 minutes instead of several hours. He has also seen AI used in grading, mechanical engineering and circuit design in electrical engineering.

“AI will be one of the most important technologies we have developed, and it will impact us in ways we can’t yet understand,” Walters said. “It’s kind of like trying to guess what the internet was going to become in the 1990s.”

In addition to consolidating text, Jacob sees significant opportunity with AI’s ability to synthesize information across different data types including text, semi-structured data, graphics, drawings, models, photos, video and audio.

“I think that is a real opportunity [to be able to apply] all the structured, semi-structured, and different types of data and see how it is being applied across other industries,” Jacob said. “I also want to underline that this is going to take all of us in the industry coming together as we go into this season of innovation with AI.”

As with every technology and tool that has come from AI, quality is essential. AI tools will only be as good as the information used to “train” it.

“Great AI comes from great data,” Lazzarotto said. “More than ever, we need to remind the whole AEC/O industry that today’s data is still locked within files, workflows or processes that need to be open.”

Even if you’re not ready to fully invest in AI tools, it’s time to prepare for the inevitable integration of artificial intelligence into the construction industry. These tools are set to revolutionize the way projects are managed, offering enhanced value at reduced costs, fostering collaboration and addressing productivity challenges that have long plagued the sector.

Here’s how construction firms can begin preparing for AI adoption:

Identify pain points: Assess your current operations to pinpoint areas where AI can provide solutions, such as optimizing scheduling, reducing errors in designs or enhancing safety protocols.

Invest in data infrastructure: Lay the groundwork by ensuring robust data infrastructure. Even if AI deployment is not immediate, having high-quality data is crucial for effective AI implementation in the future.

Strengthen data management: Implement stringent data management practices to ensure data quality and accessibility, which are essential for AI algorithms to function effectively.

Monitor and evaluate: Stay informed about advancements in AI technologies and their applications in construction. Learn from industry peers and competitors to stay ahead.

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Upskill the workforce: Invest in training programs to equip your team with the skills needed to leverage AI tools effectively. Focus on nurturing talent that can integrate AI into daily operations.

Start small: Begin with pilot projects to test AI applications in real-world scenarios. Collaborate with AI experts or partner with technology firms to navigate initial implementations.

At Bluebeam, our commitment to innovation drives us to explore new ways technology can streamline processes in the architecture, engineering, construction and owner (AECO) industry. By addressing the industry’s challenges, we aim to improve the lives and work of professionals involved in building our world.

“Our objective is to propel the industry forward,” explains Don Jacob, Bluebeam’s chief innovation officer and co-founder. “We aim to create pathways for progress.”

AI lies at the heart of our recent innovations, exemplified by three AI-powered tools designed to save time by automating mundane tasks:

Auto Align: Simplifies the intricate and error-prone task of aligning points on drawings.

Automatic Title Block Recognition: Extracts critical information from drawings to automate title block creation.

3D Drawings: Transforms flat drawings into immersive 3D models, providing new perspectives on project visualization.

Looking ahead, as we continue to explore AI and other technologies, we’ve launched Bluebeam Labs, an innovation sandbox where collaboration with our users shapes future solutions before their global release.

“Given the rapid evolution of technology, there’s a significant opportunity for collaborative problem-solving within the industry,” Jacob emphasizes. “We’re committed to partnering closely with our customers to refine and optimize these tools.”

By embracing AI, construction firms can not only enhance efficiency and reduce costs but also drive innovation across the sector, paving the way for a more agile and productive future.

Maybe you’ve been there—the music is bumping; the vibe is right. Many people could spend all night on the dance floor in a happening night club, especially when they’re young—if only most dance clubs weren’t so hot. Those sweaty, packed clubs might not be the most comfortable places to be, but as Glasgow-based venue SWG3 has discovered, such heat-generating hot boxes can be a potent source of clean geothermal energy.

Built spoke to David Townsend, director and founder of the award-winning geothermal energy consultancy TownRock Energy, about how one dance club has become an unlikely power source.

An unusual power source

Townsend has nurtured a lifelong fascination with geothermal energy. “My whole career, since founding TownRock Energy in 2013 right out of university where I studied geology, has been focused on exploring and applying all of the ways that heating and cooling can be provided from technologies installed in the ground,” he said.

Because of his passion for all things geothermal, it’s no surprise that the concept for SWG3’s innovative body-heat-powered dance floor came to him long before he consulted with Andrew Fleming-Brown, SWG3’s owner, about transforming the arts and events venue into the world’s first geothermally powered night club.

“The inspiration started when I was overheating at the front of a music gig in a poorly ventilated club and realized how much heat is given off by the crowd,” Townsend said. “But the idea didn’t fully materialize until my first meeting with Andrew.”

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Once the two put their heads together, they realized that all that power Fleming-Brown’s dancers and event attendees were generating could be put to good use.

“This type of geothermal energy technology has many advantages,” Townsend said. “It’s very high efficiency. Typically, one unit of electricity in gives four to five units of heat out, which increases when the boreholes have been previously heated up during a cooling cycle. It also has minimal surface impact, since all of the new plant is contained within a repurposed shipping container, and the rest of the infrastructure is all buried underground and silent.”

On top of that, Townsend’s storage solutions mean that all the energy the system is generating will be put to good use. “Nothing is wasted,” he said. “Using geothermal storage allows for heat to be stored over days, weeks, months and even years, as opposed to hot water tanks, which store for a mere couple of days, or air-conditioning, which does not store any heat.”

Making the dance-floor-powered club a reality

While the concept of a dance-floor-powered space might have been intuitive, Townsend said it took creativity and thinking outside the box to turn the idea into reality.

“Every dance floor that has hundreds or more people and good music generates heat, but capturing this heat and storing it for use another day is an innovative process,” Townsend said.

First, the system must efficiently remove heat and moisture from the occupied space, so the process can begin. “Air-conditioning units in the ceiling, which remove heat and moisture from the air, transferring the heat into refrigerant, which runs through pipes to the heat pumps,” Townsend said.

From there, the heat travels throughout the club. “The heat pumps transfer the heat to a 2.5 km loop of vertical borehole pipes via a water-based circulating fluid,” Townsend said. “This cycle can be reversed to bring heat back out of the ground and into the dance floor (literally, as it also connects to underfloor heating).”

At the end of its journey, the heat is efficiently stored until it is needed to provide energy. “Heat is stored underground in the rocks beneath the community garden,” Townsend said.

After designing the system, construction began. “The construction program, including tendering to secure contractors and permitting, ran from July 2021 through to August 2022,” Townsend said. “COVID and the associated meltdown in the global supply chain caused a few headaches and delays.”

Once those delays were resolved, “90% of the construction itself was carried out from January to June 2022,” he said, before the club was ready to open. “The system has been operating since September 2022,” Townsend said, later adding that, “patrons have been excited to hear about the technology, and the story has been incredibly well received on social and mainstream media.”

A greener, groovier future

“This is the first time that geothermal boreholes have been used to store body heat from dancers in a club,” Townsend said. But he hopes that it won’t be the last.

“All venues should be using this technology in some form, so as to eliminate fossil fuel use for heating and hot water,” he said. “The biggest barrier we are facing is that most venues do not own their building and the landlords are challenging to engage.”

With an increasing number of governmental organizations valuing green energy and building technologies, future incentives like subsidies and tax credits could help persuade venue owners to adopt similar solutions, or at least take a second look at areas where their spaces could easily go green.

Ultimately, Townsend said he hopes SWG3 will inspire construction professionals outside the nightlife world to take a closer look at the natural sources of clean, geothermal energy that surround us. “We hope this inspires everyone to think about how waste can be repurposed to have value,” Townsend said. “In cities waste heat is everywhere, and if we captured, stored it in the ground and reused it we would be able to eliminate the 30% of our carbon emissions that come from heating and cooling buildings.”

Imagine the impact if one construction method could help solve the housing and labor shortage, decrease the economic costs of chaotic weather damage and help families build generational wealth.

Jim Ritter, founder of Printed Farms Florida, believes 3D-printed buildings can radically change the construction industry to achieve those goals. In 2023, his startup completed the world’s largest 3D-printed building, a horse farm in South Florida.

With 3D-printed construction processes, Ritter sees opportunities for contractors to build faster, more sustainable and cost-effective buildings that reduce the impact of severe weather events. Here, he shares the details of the 3D-printed facility serving as a model for the industry.

A big undertaking

In 2020, Ritter’s Printed Farms built its first 3D-printed structure, a tractor shed, and then in 2021, a house in Tallahassee. Ritter, a lifelong equestrian, then set his sights on using the construction technique to build a horse facility.

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The company’s third project, currently the world’s largest 3D-printed structure, is a 10,600-square-foot luxury horse barn with 16 stalls, a 2,100-square-foot hot walker and a manure bin, among other features. He used a COBOD 3D-printer with an Mtec pump/mixer system to extrude a 3D mortar mix to build the structure layer by layer.

“Our printed mortar material is 6,000 psi, compared to the average building material of 3,000 to 3,500 psi, so we have a much stronger, denser material,” he said.

According to Ritter, the materials used in 3D printing create a cooler building. The design includes a cavity and air gap in the walls, which provides natural cooling. Though this was in a horse barn, these benefits also carry over to residential and commercial buildings.

“The R-factor on a block building is an R-6,” he explained. “When we do our natural wall with no insulation, we’re at R-12, and it’s easy to get to R-20.”

The economic impact

A 2019 Congressional Budget Office report estimated that the cost of damage caused by annual hurricane winds and storm-related flooding total $54 billion across the residential and commercial sectors.

“Our walls are almost impervious. You might still need to paint and air out a building and replace furniture, but the foundation is still there,” Ritter said. “We’re trying to build buildings that can withstand these climate events so it can be passed on to the next generation to help families create generational wealth.”

The long-term payoff of technology is that it will hopefully reduce construction expenses. Ritter noted that many people expect it to trim costs by 30-40%. However, the technology is still in its early stages, and Ritter anticipates the cost savings will come from the ability to build better structures with fewer people.

“In the region where this barn was built, the average building cost is $200-250 per square foot,” he said. “We came in at $220 per square foot and feel good about that.”

The learning curve

There are a lot of challenges that come along with being “the first.” Building the world’s largest 3D-printed facility was no exception.

“We had to move the machine five times, and it was challenging to get laborers to do things the right way because they’ve never built a building this way before,” Ritter said. “It is all part of the growth process, and we’re in an R&D period right now based on what we learned from the project.”

One unexpected challenge was adapting work schedules and getting the right number of people on the job. Once the machine starts printing, stopping before the “day” is done is inefficient. On this project, Ritter and the small group that worked alongside him spent long hours working in the sun without breaks.  

“This was something we hadn’t thought through,” he said. “So, now we’re working on addressing those issues to be more efficient.”

Another area for innovation is the final look. 3D-printed buildings don’t look “perfect,” Ritter explained. Some people like the look, and others stucco over it.

“We’re currently testing a paint system to produce a smooth stucco look and insulate the building on the outside all in one application,” Ritter said. “Instead of doing those three things, you spray it on and smooth it out like stucco all in one step.”

An eye to the future

Those who advocate using 3D technology in the construction industry say it will create opportunities to build structures that are cheaper and safer more quickly and require less physical labor and fewer materials in a range of architectural models and shapes. “I say 3D printing is like the old story of John Henry and the steam engine. He beat the steam engine in laying track, but he died of exhaustion,” Ritter said. “You can’t beat these machines as they get smarter, and I think you’re going to see other materials used so that we’re not cutting down trees just as concrete has to be more environmentally produced.”

The age of artificial intelligence is upon us. Ever since OpenAI unleashed the inaugural public version of ChatGPT, its innovative generative AI tool, in November 2022, use of the technology has boomed, with nearly every industry investing  to discover current and future uses and applications.

Companies in the architecture, engineering, construction and operations (AECO) industry are also wading into the fascinating world of AI, harnessing the tool to limit mundane tasks and streamline work.

Potential AI uses in the industry include:  

Analyzing Data: AI can analyze swaths of data to identify patterns and uncover insights that were previously stored away in scattered drawings, files, invoices and safety reports. AECO companies can use this information to improve design accuracy, streamline project management, bolster safety, optimize energy consumption and calculate sustainability metrics.  

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Iterating on Designs: With AI-powered software, AECO companies can quickly update and iterate on designs, testing out the appearance and performance of different features and allowing for easier collaboration with owners and other stakeholders.  

Optimizing Facilities Management: Using data from sensors and smart meters, AI can adjust heating, cooling and other energy use based on real-time occupancy data and climate information. The technology allows building owners to reduce energy consumption, operating costs and environmental impact.  

Creating Content: AECO companies are using AI to fine-tune proposals and client emails, as well as organize and annotate meeting notes and transcripts. 

“Construction and building is a complicated process,” said Don Jacob, co-founder and chief innovation officer at Bluebeam. “It’s got laws of physics that impact it. It’s got people and scheduling challenges. There are costs and all sorts of other factors that contribute to the successful completion of a project or not. And I think that’s where AI has the potential for this very wide scope of ways to impact problem-solving. It’s a unique tool, a multidimensional tool that can help us identify new ways to complete projects.” 

Time will tell where the construction industry is headed with AI. But it appears many companies in the industry have already taken advantage of it to improve workflows and make their project teams run more efficiently at every level.

In 2022, the visual generative artificial intelligence (AI) tools Midjourney and DALL-E hit the scene, both letting creators input text prompts to bring wild conjurings to life as realistic renderings. According to Stanislas Chaillou, author of “Artificial Intelligence and Architecture,” AI is the latest major development in architectural technology. Although it’s easy to get swept up in the glitzy generative side, designers are finding many more ways that AI can expand creativity while saving time, money and brainpower for more rewarding tasks.

In London, for example, the Applied Research and Development Group (ARD) at Foster + Partners began applying AI and its offshoot machine learning (ML) in 2017. The group used it for models ranging from design-assist, surrogates, knowledge dissemination, business insight—and, yes, its own take on diffusion models that generates images from natural language. Los Angeles-based Verse Design tapped AI to meet aesthetic and performance criteria for a structure that recently won a 2023 A&D Museum Design Award.

But implementing AI doesn’t come without obstacles—including questions about protecting intellectual property (IP), training with appropriate datasets and defining creativity when it seems to lie with the designer of the AI script.

AI design assistance arrives

One ARD Group study involved laminates that self-deform when subject to temperature, light or humidity. The materials would enable a façade that responds differently depending on conditions to provide shading, prevent overheating or increase privacy. But to simulate the laminates’ nonlinear and unpredictable response, the group turned to ML.

“We used ML to predict how a passively actuated material would react to variable temperature changes,” said Martha Tsigkari, senior partner. “With the help of our bespoke distributed computing and optimization system, Hydra, we ran thousands of simulations to understand how thermoactivated laminates behave under varied heat conditions. We then used that data to train a deep neural network to tell us what the laminate layering should be, given a particular deformation that we required.”

Predicting material deformation was just one application. To help automate mundane tasks and turbo-power productivity, the ARD Group is working on many more ideas around AI-powered design assist tools.

Verse Design faced similar performance constraints when designing the façade of Thirty75 Tech. The designers needed to find the optimal pattern of louvers to mitigate heat gain and meet California’s Title 24 energy efficiency standards.

“The final geometries were generated parametrically with real-time simulation data,” Tang explained. “The geometries were fed back to the energy model to find and confirm the most energy-efficient combination of louver variations that met the intent of the visual expression and performance objectives.”

Extraordinary content delivered faster

Foster + Partners has also used surrogate models to replace slow analytical processes—and keep costs in check—when exploring the impact of changing design variables. These ML models train on huge datasets to deliver a prediction that is sufficiently exact and, most critically, available in real time. In early design stages, the surrogate model lets designers balance accuracy with the ability to make sound decisions sooner.

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Foster + Partners’ in-house application programming interface (API) lets clients connect from digital content creation tools. With these plug-ins, users can run predictions directly. The interface also lets designers deploy diffusion models like Midjourney to stir imaginings.

“The capability of these transformers-based models to describe images, understand their context and make suggestions based on it has moved the discussion from image manipulation to natural language processing for content creation,” Tsigkari said.

Intellectual property creates a conundrum

Some creators express concern about losing control of intellectual property when feeding their own assets into AI apps. For instance, class-action lawsuits against software providers contest use of copyrighted images to train systems. Tsigkari stressed the need to understand security and IP considerations and read terms and conditions before using any software. But the challenges go beyond IP.

“It is not only the fuzzy boundaries around IP that are argued,” she said. “The lack of robust legal frameworks to deal with AI and ringfence how data may be used are going to challenge how these technologies are implemented.”

Tang doesn’t have the same concerns about IP. “As Voltaire said, ‘Originality is nothing but judicious imitation,’” he commented. “The idea is not to mindlessly copy but to critically apply the technology as a tool with generative capabilities. It requires that human intellectual and critical content to tease out the real meaning to us as designers and therefore become something slightly different.”

Input determines outcome

Given the dependence of AI output on the data that are input for training, another consideration for Tsigkari is the quality of AEC datasets. “There is one universal truth behind AI: data is king,” she said. “If we want to use and control these technologies to the best of our ability, we need to learn to control the data that drives them first.”

She noted the need for consistent tagged building datasets that are “contextualized, socially appropriate, structurally viable, sustainability sensitive and code complying. Our first challenge is to collect, organize and process our data across disciplines in a meaningful manner so that we can leverage it. Deploying in-house trained—rather than pre-trained—models is also a very robust way of ensuring the quality of your results,” she added.

Creativity balances AI and CHI

As AI becomes more embedded in the work of architecture, how does the definition of creativity change? Tang evoked the “Star Trek” character Data when discussing the imperative of human agency to refine the outcomes AI generates. “Data is an artificial intelligent being constantly looking for the human side of himself,” Tang explained. “I don’t think AI can ever supersede or replace human intelligence, particularly CHI.”

Tsigkari noted that humans have the upper hand on several qualities that enable creativity—including aesthetics, emotion, collaboration, communication and responsibility. “We should be focusing on how AI can become a creative assistant that is augmenting, rather than replacing, creativity—and the values we bring to the table are driving the changes we want to see.”