AI Startups in AE&C (Architectural, Engineering and Construction)
Riccardo Cosentino
Leading with a purpose. | I bring innovative, technical and financial solutions to large, complex infrastructure programmes at every stage of their lifecycles.
Gatekeeping this data will only slow the adoption rate of artificial intelligence (AI) in megaprojects.
Between my recent return to Sa?d Business School, University of Oxford for Post Graduate Diploma in Artificial Intelligence for business and my upcoming speaking engagement on “What drives successful AI adoption?" at the World Summit AI in Montreal this month, it’s reasonable to assume you’ll be hearing much more about artificial intelligence from me—particularly regarding its interaction with engineering and construction. Personally, I have been fascinated with the current AI startups (and gaps) in the AE&C sector globally.
So, as one does (or at least I do), I conducted a thorough research report to better understand the future of my industry and megaprojects as a whole, starting with compiling an exhaustive database of 113 AI startups and software offering AI solutions in Risk Management and Safety, Operational Efficiency, Quality Assurance, Asset Management and Maintenance, Communication and Collaboration, Sustainability and Environmental Impact, Data Analytics and Decision Support, Innovative Materials and Methods, Design and Planning and Robotics and Construction Automation leveraging AI technologies like Automation, Robotic Process Automation (RPA), Generative AI, Predictive AI, Machine Learning, Natural Language Processing (NLP) and Computer Vision.
First, I did a simple desktop research/Google search to find out the AI startups and Software in the construction and engineering sector, before deep diving into the company website to find out the AI application and AI technology.? Situations where the AI technology and AI application was not directly available on the website,? third party sources like articles by individuals, VCs and Research companies were utilized to secure more details, as well as my own understanding of AI technology to classify. The funding round information is taken from public sources like Crunchbase, Tracxn, Articles and Publications.?
I then leveraged this exhaustive database and secondary research where I have explored research articles and reports to compile our findings on the trends in the AI applications and the gaps in the AI application where there is a potential to leverage AI for increased profitability.
The research suggests that AE&C is the biggest industry owing to its USD 12 Trillion size, however it has been traditionally slow in adopting disruptive technologies like AI and has relied on manual processes thus making it vulnerable to skilled labor shortage, project management issues (delays, over-budgeting, sound familiar?), sustainability and environmental hazards challenges. The economic uncertainty is another looming challenge that is pressing the industry to squeeze the cost.
The AI applications in the AE&C sector have potential to cater to these challenges at much lower cost. This research report analyzes the emerging AI startups and software in the AE&C sector and the use of their AI technology. I have also developed a dashboard that visualizes the cross category analysis, enabling us to see the pattern.? In the trend section of the report, I was able to identify the industry needs and challenges that each AI application category is resolving and current trends. While the Gap section identifies areas where AI can be tapped further to explore potential use cases. The adoption of AI and the current use cases are still pretty nascent which is why it became integral to study the trends and gaps which poses an opportunity for new startups to launch, developing new use cases.
AI has been transforming the way many industries are operating through its disrupting technologies that free up humans from redundant tasks so they can focus on more intelligent tasks and delegate the boring work to the AI which results in large cost and time saving.
The AEC sector has traditionally been a labor intensive sector which relies largely on humans and hence the long standing challenge of the skill gap in the industry has led to increased expenses, delays and low productivity. The latest findings from the Associated General Contractors of America (AGC) and Autodesk indicate that an overwhelming 80% of construction companies are encountering significant challenges in recruiting skilled workers for hourly craft roles [1]. By leveraging AI and automation, this gap can be bridged to a large extent.?
The Global Artificial Intelligence (AI) in Construction Market is valued at USD 594.6 Million in 2022 and is projected to reach a value of USD 4,909.7 Million by 2030 at a CAGR (Compound Annual Growth Rate) of 35.2% over the forecast period 2023-2030 [2].
Trend Identification
Construction is a complex and a lengthy process, and each phase has its own challenges. AI technologies are harnessing the power of data to automate the lengthy and redundant processes at each stage of construction. Same is reflected in our database where we can see the AI application and adoption across the multiple phases of construction from Pre-Construction to the final delivery.
AI Opportunities in the Design & Planning Phase
The design and planning phase which happens before the actual construction commences, has traditionally been human dependent and a redundant process with lengthy testing and prototyping involved.
The rise of AI technologies like Generative AI can be seen disrupting the area through automated construction design, estimate and schedule generation with accuracy and sustainability factor kept intact. One of the key trends indicated by the Deloitte 2024 Industry Outlook Report is that digitization and generative AI are foundational for value realization in the industry [3].
In the Database, I have captured almost 17 AI software and companies that are helping in automating building design, schedule, construction documents, identifying flaws in design, and generating sustainable design options leveraging AI technologies like Generative AI, Computer Vision, Robotic Process Automation (RPA), Automation and Machine Learning. For example, Dusty Robotics is using a robot leveraging AI to generate layouts.
The AI technologies in the Design and Planning stage reduces the review time while generating multiple alternative designs in a matter of minutes and increases the accuracy of estimates so much so that there is only little to no room for error left. As per Deloitte’s survey, AI in design review can reduced budgets and timeline deviations by approximately 10-20%, along with a decrease in engineering hours by 10-30% [4].?
Currently, the Design phase is one of the most revolutionized areas which is harnessing the power of learning algorithms and generative AI to analyze vast datasets, identify patterns and optimize designs that save time, reduce costs and provide a better baseline of information for human experts to carry forward.
?AI Opportunities in Project Management
Project management in the Construction and Engineering industry is a set of multiple technical and collaborative tasks. Project management is also one of the key areas where a lot of challenges, including meeting deadline, streamlining operations, task allocation and collaboration and communication, arise with almost 16% projects end up being over-budget [5].
Currently the industry is harnessing the powers of AI to mitigate these challenges through Workflow automation, Scheduling, Remote Progress Tracking, Remote Quality Assurance, Automated Timelines Adjustment, Automated Material Requirement Alert etc. via AI applications like Digital Twin and Reality Capture harnessing technologies like Computer Vision, Robotic Process Automation (RPA), Machine Learning and Natural Language Processing (NLP). The successful implementation of AI in Project Management is evident by the fact that in my sample data, the AI in Project Management comprises of more than 35% of the total market value of AI solution segment in 2022, where AI solution segment value was USD 15.1 Billion globally [6] and the demand for AI in Project Management is forecasted to increase [7].
Cost volatility is another key issue that the industry is facing which is a result of lingering uncertainty in the industry and can lead to complicate project planning, project management, and even terminate or delay the project delivery. Some companies even sought to change the scope based on the varying material and labor cost. The AI solutions that are improving Operational Efficiency and Quality Control through Automation and Remote Monitoring are very much helping the industry meet the cost control challenge which is a high priority today, as these solutions reduce labor cost in more than one ways. Also, as the AI solutions improve accuracy and speed they mitigate the cost of redoing a wrong job and the cost associated with lengthy processes done manually.
Another key element in Project Management is communication and collaboration. As the construction projects are spread out on site and in offices, communication becomes hassle and ineffective communication can contribute to project delays and inefficiencies. The AI Project Management software is helping in reducing the friction in communication through real-time progress tracking and sharing options. Teams can access site progress from anywhere in the World, and can see the notes left by other team members, and can even assign other team members tasks on the same tool.
The database also reflects that Project Management (Operational Efficiency, Quality Assurance, Collaboration & Communication) is indeed an area where a lot of AI startups and software have emerged. Almost 50% of the tools in our database are providing AI solutions in Automated Workflow, Construction Documentation and Verification, Progress Tracking, Cost and Material Estimate Automation, Site Inspection, Communication and Collaboration and End-to-End Project Management via AI Applications like Digital Twin, Reality Capture and Learning Algorithms utilizing technologies like Computer Vision, RPA, Machine Learning and NLP.
There are some tools like Pace OS by Teknobuilt that are providing End-to-End Management while others are offering more targeted solutions. We also found a couple of innovative and stand out AI software like Converge.io and AICrete that help in appropriating Concrete Mix to reduce Carbon Footprint, control Cost and improve Quality Assurance. While most of the Computer Vision and ML powered tools for site inspection and progress tracking offer features that enable collaboration among team members, we found some unique tools like Buildwise, DeepHow, and Document Crunch which facilitate knowledge sharing among team members leveraging NLP.
AI solutions in Operational Efficiency, Quality Assurance and Collaboration and Communication hold the top three positions in the market composition of the database as well.
AI Opportunities in the Asset Management & Maintenance Phase
AI is enabling managers to monitor the Assets remotely without ever having to visit the site, saving them cost and time. The AI technologies used in Asset management is very much the same as being used in Project Management (Quality Control) which is Computer Vision, RPA and Machine Learning.
Techniques like Reality Capture and Digital Twin helps managers have a virtual model of the site ready, and with the help of Computer Vision technology they are able to identify any damages that might have occurred on the site and need maintenance.
The Database reflects such tools and software that are helping Real-estate owners monitor and inspect the assets remotely. Leveraging Computer Vision and ML, the system alerts them upon occurrence of any damage. For example, Spotscale, Nuuka and H3Zoom.ai.
Advanced AI and Machine Learning are helping in conserving energy while monitoring facilities, as they have the potential to identify and switch off unnecessary running ACs, lights, and other energy consuming appliances without human involvement.
AI Opportunities in Risk Management & Safety
A key trend has been to invest in AI technologies that can perform more value-added operational tasks, making processes faster and accurate, instead of just automating repetitive tasks. Therefore, AI can be seen integrated into quality assurance and risk management tasks where AI can help prevent costly mistakes by analyzing data and predicting the risks in advance [8].
With Construction being a labor intensive field and its risky operations put the labor force at risk of accidents that could result in life changing injuries and even fatal sometimes. The predictive AI technology is helping the industry mitigate risk and improve workforce safety on-site. Many companies are coming up with wearable devices and sensors, harnessing the power of computer vision and predictive AI,? that alert the workforce when they are near a high-risk area. For example, Kwant.ai
The Database reflects AI tools and software that are offering solutions in Risk Management & Safety. Some of these solution providers are offering wearables that send alerts upon reaching a risky spot, some monitor and inspect the site and identify the risky areas in advance leveraging Computer Vision and Predictive AI, and some monitor the site and identify if the labor is not wearing the safety harness.
The use of Robotics in Construction is also reducing risk of human casualties by automating risky operations.
AI Opportunities in Construction Automation & Robotics
Due to the traditional labor intensiveness in the construction operations, the safety risk and skill gap are two looming issues that the industry faces. Shortage of skilled labor has been an ongoing issue which hampers the firms’ ability to meet the deadlines. Almost 68% of the firms surveyed, found to be struggling to fill open positions while 1/5th of the construction workers are older than 55 who are considered to be skilled labor [9].
Both of these needs are effectively met by Construction Automation and Robotics, leveraging AI. Especially with the foundational technology framework already in place and developed, Robotics and Automation using drones, sensors, IoT devices and autonomous guided vehicles are paving their way to carry operational tasks like site inspection, material delivery, brick laying, painting and installations.
The use of robots in construction is in itself a rising trend, but if we go deeper we find that the use of mobile robots like robotic arms, drones, and those that can literally cover more ground by aiding excavators, is getting popular as the industrial robots [10].
领英推荐
Similarly, the use of customized robots which are designed for particular needs is getting popular, however customization also limits their functionality [11].
Cobots, short for collaborative robots, are engineered to work alongside humans who are able to adapt to changing shifts, and absorb complicated instructions. There are continuous efforts being made to advance such robots in complicated construction procedures [12].
My database reflects construction robots, mobile robots, and swarm robotics providing solutions for heavy vehicle and excavator automation, site monitoring, construction layout, site mapping, painting, drywall finishing, bricklaying, tile grouting, tunnel construction and insulation laying leveraging Machine Learning, Computer Vision, and Robotic Process, Automation (RPA).
AI Opportunities in Innovative Material and Methods
Modular and Prefabrication construction methods and 3D Printing techniques are gaining traction in the construction due to the increased speed, decreased cost and improved sustainability, leveraging AI and Robotics.
My database reflects startups that are offering innovative materials and methods in construction. Some of them are producing prefabricated building component using AI and Robotics like BotBuilt,and Ecoworks, Some are leveraging 3D printing like Icon, and remaining are leveraging AI and Machine Learning to produce Concrete Mix that improves quality and reduce Carbon Footprint like Mixteresting.
AI Opportunities in Sustainability and Environmental Impact
Buildings account for 30% of global energy consumption and 26% of global energy-related emissions, as per the International Energy Agency. With the advances in development of?efficient building materials and sustainable construction practices and their increased adoption, the industry is expected to be aligned with the International Energy Agency’s Net Zero Emissions by 2050 Scenario, which requires all new buildings and 20% of existing structures to be zero-carbon-ready by 2030 [13].
According to the US Green Building Council’s 2023 report, sustainability is a top priority for most surveyed E&C firms, as it aligns with their organizational mission and business strategies [14].
AI is enabling the reduction of the environmental impact of construction projects by forecasting and minimizing carbon emissions, transitioning to greener materials and reducing re-work [15]. AI is being harnessed to generate sustainable and energy efficient building designs that reduce energy consumption by making the most of natural resources like day-light leveraging generative AI. Machine Learning is being utilized for Concrete Planning, Carbon Mineralization and to monitor CO2 emission.
My database reflects companies leveraging AI to build products that can minimize carbon emission and improve sustainability in the construction processes. View is leveraging AI to develop smart windows that are day-light responsive, while there are quite a few that are leveraging generative AI to produce sustainable building designs, some like Teknobuilt are using ML to track carbon emission and optimize carbon footprint. There are companies like Caidio that are providing concrete intelligence and AICrete that are providing concrete mix design for a sustainable building material. Most of them are leveraging ML, but some are also using Computer Vision and RPA.
AI Opportunities in Data Analytics and Decision Support
With the advancement of digitization in the Project Management area, there is an influx of site data that AI and Machine Learning are helping in making sense to support decisions. Data analytics at the project level is becoming a reality, and leading firms are beginning to utilize machine learning algorithms for insights and informed decision-making [16].
The database reflects AI startups that are providing cutting edge Data Analytics solutions leveraging Machine Learning that support decision making. They are providing AI insights into Project Progress and Concrete Intelligence helping the executives making strategic decisions.
Gap Analysis
The AE&C sector has traditionally been slow in adopting AI as compared to other industries, which is why the current use cases of AI in the industry are all pretty nascent and can be modified to be more accurate. Although, in the current use cases we can observe that there is more shift towards Project Management AI solutions which are continuously enhancing the Project Monitoring and Planning. This trend is also reflected by our Database which is 50% composed of Project Management (Operational Efficiency, Quality Assurance, Collaboration & Communication) solutions.
In our secondary research, we were able to identify the areas where AI solutions can benefit the sector even more.
AI Opportunities in Data Provision/Synthetic Data
Most of the AI learning algorithms are based on learning from the past and thus require a heap amount of previous project data to be trained on. Firms struggle to continuously feed machines the site data and this puts the large firms at benefits due to the volume of their previous project data.
However, this gap poses an opportunity for an external third party to enter and leverage AE&C data to train its models—a scenario that would likely result in improvement across the industry as a whole but limited competitive advantage for individual firms. Although, due to current restrictions on data sharing, this is not an easy field to navigate through [17].
A plausible solution to data scarcity could be generation of synthetic data in construction management which can provide useful insights regarding the underlying non-linear relationships [18].
AI Opportunities in Advance Data Analytics
Supervised Machine Learning has emerged as the most influential AI technology specially in Safety Management, and can help identify pattern, insights and correlation. If properly trained on past data, it can make sound predictions that can support decision making. The industry can totally tap the supervised Machine Learning algorithms and increase profitability by leveraging a backlog of project schedules, as-built drawings and models, computer-aided designs, costs, and invoices, among many other data sources that are already being generated by the industry [19].
AI Opportunities in Modular Construction
Modular and Prefabrication construction is certainly an area where value can be added using AI. AI can enhance precision, quality and methodisation in installation, and can even use to improve training on how the different components, frames and interfaces for modular come together both in the factory and on-site [20].
My database also reflects that the least number of software and startups are found in the innovative material and method category.?
AI Opportunities in Waste Management/Sustainability
As discussed in the Trend Identification section, sustainability is one of the most focused areas in the Construction and Engineering industry due to the continuous and large amount of waste being generated by the industry and the pressing requirement of the regulatory institutions to bring emissions to Net Zero.
AI has impressive applications in bringing sustainability to the construction process, which are still largely untapped. Waste Analytics can leverage AI to turn the information gathered from data sources such as building design, material component and construction processes and can turn the information into waste management strategies such as optimization of offsite construction, material selection, reuse and recovery, waste-efficient procurement, deconstruction, and flexibility [21].
A gap that we found during our research was less availability of tools leveraging AI to build up a database of sustainable? and alternate raw materials. Circularity is a growing trend in the built environment where reuse of material and design for deconstruction is highly encouraged. However, to enable more firms to reuse material, there is a need for high level material passports - documented directory of reusable materials which stimulate the reuse of material, avoids material destruction and improves waste management [22].
Our database also reflects that this area is still untapped as the sustainability and environmental impact startups and software comprise 10% of the total market composition.
AI Opportunities in Communication & Collaboration
AI can play a key role in standardizing and digitizing the engineering changes approval process, contract management, communication and notification and can enable the AE&C companies to carry out these procedures remotely and quickly accurately, saving them costly errors and redo [3].
Although many AI solutions in Operational Efficiency and Quality Control are providing features that facilitate remote collaboration, there are still less tools that are focused entirely on contract management and team collaboration as reflected in our database.
The Future of AI in Engineering and Construction?
The AE&C industry is a whooping USD 12 Trillion industry making it the biggest industry globally. Yet the industry has been slow in adopting AI and new technology to improve its operations and hence have lingered on to manual processes which has made the industry vulnerable to challenges like skilled labor shortage, project delays, and over-budgeting. With the economic uncertainty looming and fluctuating material and labor cost, the industry has further faced the pressing challenge of controlling cost to avoid changing scope every now and then. Furthermore, the industry is one of the biggest contributors to climate change due to unsustainable practices and raw materials.
The advancement of AI has full potential to disrupt the industry as the AI solutions can reduce the challenges by a considerable magnitude. Especially after the emergence of generative AI in 2023 the AI applications in the AE&C became disruptive with full blown automation in the design and planning phase. There are many startups that have emerged offering solutions Worldwide leveraging AI technologies like Machine Learning, Predictive AI, Computer Vision, RPA, NLP, Generative AI, Automation and more that have helped the industry tackle the issues smartly.
Robotics and Automation has enabled firms to deal with skilled labor shortage and has let them put their smart human workforce on more value added tasks by delegating the repetitive work to AI. Digital twin and Reality Capture techniques have leveraged Computer Vision, ML and RPA to enable the AE&C firms to remotely monitor sites and collaborate on quality assurance, saving them time and cost to visit the job sites. Sensors, IoT devices and wearable devices are leveraging Computer Vision and Predictive Analysis to alert the workforce on jobsite regarding risky locations, improving worker safety and risk management to unprecedented scale.
Even though the AI startup universe is wholesome, it still is a long way to go given the size of the industry and the pace of the AI adoption which is still considered slow and predicted to be moderate in the near future. The AI adoption in the industry is hampered by certain challenges like availability of structured data and talented workforce. Hence, the industry needs to work on the gap to improve the pace of AI adoption in order to uncover the potential use cases of AI in Construction and Engineering. Let's follow Tesla's lead and accelerate AI adoption by openly sharing our knowledge—it benefits everyone.
References:
AI Consultant. AI for projects.
10 个月Wow , what a resource.