AI in Construction: A Comprehensive Guide for 2024

AI in Construction: A Comprehensive Guide for 2024

Artificial Intelligence has become a powerful force in many industries, including architecture, engineering, and construction.

Despite the notorious resistance to new technologies, just between 2020 and 2022 construction and architecture companies invested $50 billion in AEC tech. After decades of sluggish development, the AI wave is finally reaching construction sites. 

In this guide, we will explore how AI in construction is already used and how you can leverage these technologies to stay ahead in the industry. 

How This Guide Will Help You

In this guide, we will look at different ways in which AI is making construction better:

  • Risk Management: We'll explain how AI can predict problems before they happen.
  • Project Monitoring: We'll see how cameras powered by AI can monitor and control projects in real-time.
  • Project Management. We’ll show how construction AI can help you with project management tasks. 
  • Safety Tracking: We'll talk about how AI can help track safety on construction sites. 
  • Productivity Tracking: We'll show how you can use AI for construction to find things that slow down work on-site and fix them quickly.
  • Design Optimization: We'll explain how artificial intelligence in construction helps you come up with design ideas and test them.
  • Plan-Build Comparison: We'll explore how you can compare plans with what's being built and find mistakes faster.
  • Site Documentation: We'll explain how AI can automatically gather and analyze site documentation.

What is AI in Construction: Machine Learning and Deep Neural Networks

AI in the construction market usually comes in two types.

Machine Learning enables computers to learn from data without being explicitly programmed. With ML algorithms, an app can identify patterns, make predictions, and automatically improve performance.

Machine learning in construction industry is used to identify hazards, improve scheduling, and even forecast maintenance issues.

Machine Learning for Contruction Operation Management
Machine Learning in Construction Industry


Deep Neural Networks are a specific type of Machine Learning model inspired by the structure and function of the human brain. These networks consist of layers of interconnected artificial neurons that analyze complex data and extract meaningful insights.

In construction, deep neural networks are used to analyze images and videos from construction sites. These apps help to identify and fix disparities between the project and results, as well as monitor the productivity of workers. 

Deep neural networks: AI in construction
 Deep Neural Networks

Benefits of AI in Construction

AI and automation in construction offer multiple benefits, including:

  • Improved safety: AI-powered tools can monitor construction sites for potential safety hazards and alert workers to take preventive measures.
  • Enhanced productivity: AI in the construction industry helps to automate repetitive tasks and optimize resource use, which boosts the productivity of your workforce.
  • Quality control: AI algorithms can analyze data to identify errors or omissions in designs or construction processes.
  • Predictive analytics: AI in construction industry can predict project delays or cost overruns, which allows you to intervene proactively before it's too late.
  • Design optimization: Using AI in construction helps to analyze design parameters. AI tools can also propose improvements, which enables you to build more robust and effective structures. 

Applications of AI in Construction

1. Risk Management

Risk management is a systematic procedure that helps you recognize, evaluate, and mitigate strategic, financial, legal, and security threats to capital and revenue. 

In construction, risk management helps to avoid costly delays and rework, and keep the environment safe for personnel.

Autodesk's Construction IQ is an example of an AI-driven risk management tool.

The system identifies and helps to prevent four types of risks:

  • Design Risk Factors. It allows project leaders to prioritize and address design issues daily. This prevents the issues from evolving into more complicated issues that require expensive construction modifications.
  • RFI Risk Factors. It helps teams to recognize RFIs that pose significant risks to the project's cost and schedule. The system categorizes them based on root cause, discipline, and building component, which allows to detect, prioritize, and resolve issues early on.
  • Quality Risk Factors: The system helps to monitor issue status, activities, and adherence to the quality standards. 
  • Safety Risk Factors: It provides project leaders with immediate insight into high-risk areas of their project, which enables you to act quickly to stop unsafe behaviors and hazards before they lead to severe incidents.

Overall, artificial intelligence in construction management allows project managers to address potential risks before they impact the project timeline or budget. 

2. Project Monitoring and Control

In construction, it’s essential to complete projects on time. Remote project monitoring and the ability to detect anomalies can significantly improve your capacity to monitor and control projects. 

An example of innovative AI-driven software is EarthCam. With EarthCam, project managers can:

  • Monitor progress remotely: Project managers can keep an eye on the development of their projects without needing to be physically present at the site.
  • Detect anomalies: EarthCam's AI algorithms are trained to identify any irregularities or deviations from the norm that may impact the project timeline.

This is achieved with the use of complex AI technology: 

  • Object Detection. The computer vision technology identifies ladders on the job site and alerts when workers are at significant heights. It also provides customized alerts based on predefined actions like working on scaffolding.
  • AI-driven Media Dashboard. The dashboard provides real-time status updates and analytics on construction personnel and equipment.
  • Jobsite Activity Visualization. The AI allows you to visualize data from millions of points to identify and resolve inefficiencies in jobsite flow. If you wish, you can also create automated heat maps of site activity, which helps to understand the density of personnel and traffic patterns. 

3. AI in Construction Project Management 

When it comes to AI in construction management, most AI-powered solutions will offer you the following features:

  • Efficient Scheduling: AI in construction scheduling can take into account task dependencies, priorities, and workforce availability. This helps to optimize schedules and reduce delays. 
  • Customized Workflows: AI creates tailored workflows to meet specific project needs. This makes sure that critical tasks are completed on time and resources are used effectively.
  • Budget Control: AI in construction estimating helps to manage project budgets, which reduces administrative workload and minimizes costly mistakes.
  • Streamlined Documentation: AI streamlines project documentation processes, which makes sorting out the documents easier and faster. 

4. Safety and Productivity Tracking

Safety is a paramount concern in the construction industry, as it involves working in hazardous environments and handling heavy machinery. With AI, construction companies can enhance safety measures and reduce the risk of accidents. 

AI systems can analyze real-time data from various sources, such as video surveillance cameras and IoT sensors, to detect safety violations and potential hazards on construction sites.

For instance, viAct uses AI algorithms to monitor construction sites for safety violations. Their system uses computer vision technology to analyze video feeds from cameras placed strategically around the site. 

Some of the notable features include: 

  • Alert System for Unsafe Acts/Dangerous Situations. The system generates alerts when it detects any safety non-compliance, unsafe act, or dangerous situation. This allows you to implement necessary preventive measures to maintain safety on the worksite.
  • Access Control for Danger Zones. The system issues alerts if a worker or any other individual enters a restricted area or danger zone. These might include areas such as holes, electrical fencing, lifting zones, wet floors, and others. 
  • Monitoring in Confined Spaces. The system oversees confined space entry access and keeps track of atmospheric changes. Furthermore, it sends out alerts in cases of extreme weather. 
  • Productivity Monitoring. ViAct's system also tracks worker activity and measures productivity. It analyzes movements, tasks performed, and time spent on specific activities. 

AI in Construction: Safety

5. Plan-Build Comparison

Plan-build comparison involves comparing the as-built conditions to the original design plans to identify any deviations or inconsistencies.

Traditionally, this process was time-consuming and prone to human error. With AI, plan-build comparison has become more efficient and accurate.

For example, OpenSpace.AI uses AI algorithms to capture the construction site on camera and compare the actual progress to construction plans. 

With computer vision and machine learning, OpenSpace.AI can identify discrepancies between the two and highlight areas that require attention. This enables construction teams to address issues promptly, which reduces rework and makes sure that you adhere to design specifications. 

How OpenSpace.AI works: 4 Key Steps

Here's a breakdown of how OpenSpace.AI simplifies plan-build comparison:

  1. Data collection: OpenSpace.AI collects data through a camera walkthrough. You just need to connect the 360° camera and walk around the site as you usually do. 
  2. Image analysis: Then, OpenSpace.AI analyzes collected images and extracts relevant details about the physical structure.
  3. Machine learning algorithms: After that, the system compares the extracted information with the design plans and identifies any disparities or variations.
  4. Deviation detection: The system pinpoints areas where deviations exist, which enables project teams to take immediate corrective actions.

With AI plan-build comparison tools, you can minimize errors and ensure that the built structure aligns with the intended design. 

5. Construction Documentation

Accurate site documentation is important to maintain transparency and accountability during construction. It is also a useful resource for audits, inspections, and maintenance later on. 

StructionSite is an example of an AI-powered platform that makes documenting construction sites easier. Here's how it works:

  • The platform uses computer vision and machine learning to understand what it sees on-site. 
  • It then organizes this visual data in a way that's easy to search and browse.

The app offers several helpful features, including:

  • Automatic photo documentation - The platform takes pictures as workers move around the site. It then analyzes these pictures and adds relevant information to them (like what part of the project they show).
  • Progress tracking - The platform also creates a timeline of all the pictures taken on-site. This helps project managers see how things are progressing over time. 
  • Virtual walkthroughs - With the platform, remote stakeholders can "walk" through the project site without actually being there.

Using AI for site documentation brings several benefits: 

  • It makes teamwork and collaboration among project teams better. 
  • It reduces the time workers need to spend on manual documentation and lowers the chance of mistakes. 
  • It keeps a visual record of all the work done on a project, which can be useful in case of disputes or during the planning of future projects.  

6. Design Optimization

AI allows to analyze vast amounts of data and generate multiple design options. This process, known as generative design, allows designers to explore creative solutions that meet project requirements. At the same time, generative AI in construction takes into account factors such as cost, material efficiency, and structural integrity. 

Generative design tools like Autodesk's Fusion 360 help architects and engineers automate the design process and create optimal solutions.

7. Building Information Modeling (BIM)

BIM is a digital representation of a building project that integrates design data with construction information. AI-powered BIM platforms provide real-time access to project data and enhance collaboration and communication among project stakeholders. 

These platforms use machine learning algorithms to analyze BIM data and generate insights that can improve decision-making throughout the project lifecycle. 

8. Internet of Things (IoT)

IoT technologies allow you to collect real-time data from sensors embedded in buildings, construction sites, and equipment. AI algorithms can analyze this data to track the location of equipment, forecast maintenance needs, or monitor waste. 

For example, IoT sensors combined with AI analytics can identify vibrations and cracks and alert you if something is wrong with the structural health of the building. 

9. Sustainable Construction Practices

Sustainability is becoming more and more important due to climate change and rising environmental standards. AI for ESG in construction can make both the construction process and the building itself more sustainable and efficient. Some ways in which AI can be used for greener construction include: 

  • Energy consumption. AI sensors can analyze data from multiple sensors, find patterns of energy use, and optimize lighting or cooling systems to reduce energy consumption. 
  • Material selection. AI can help you understand which materials will be more energy-efficient in certain environmental conditions. 
  • Construction recycling. AI can help you speed up sorting and separating recyclable waste, predict the type of materials that will be recycled the most, or track specialized waste. 

Future of AI in Construction

As the AI market is poised to reach $407 billion by 2027, the future of AI in the construction industry looks bright. 

Further Integration of AI Technologies

1. Robotics

As Kendall Jones from ConstructConnect notes: 

“The most likely scenario is that robots will be used alongside human workers to augment their work, keep them safer and boost productivity. The current capabilities of existing robots, combined with a growing labor shortage will probably lead to robots handling some of the more menial repetitive tasks, leaving the human worker to focus on other aspects of their job.”

The adoption of robotics in construction processes is set to increase. Some of the already existing, commercially available robots include ones that automate brick laying, measurement tasks, and demolition. 

Robotics used in Construction Industry
Adoption of Robotics in Construction Processes

2. Geospatial Analysis

AI-driven geospatial analysis, which allows engineers to precisely evaluate spatial relationships between assets, will help allocate resources and assess the environmental impact of projects.

The future of the AI-driven construction industry holds immense promise for innovation and advancement. Companies that implement AI today will be more competitive in the quickly evolving market landscape. 

Geospatial Analysis in Construction App Development
Geospatial Analysis


The Bottom Line

AI in construction is a quickly growing field that is poised to skyrocket in the coming years. Whether its the project management tools or advanced robots, the future belongs to businesses that embrace AI-driven transformation. 

At Apiko, we are ready to design custom, tailor-made AI solutions that cater to your needs. Whether you need a construction reporting solution or a construction asset management tool, we are ready to help you with your enterprise digital transformation.

It’s time to streamline your projects with construction digitization!