AI in Construction Has Landed

Artificial intelligence in the construction industry is here. It has emerged as a technology that is poised to transform our industry. As we enter this next frontier of construction technology, it is essential to understand what artificial intelligence is and how it offers unique solutions to advance the productivity and performance of the construction industry. 

This article provides a foundational understanding of artificial intelligence in preconstruction. We’ll explore how AI offers ways to enhance the processes that drive business for better decision-making and strategic preconstruction planning.  

What is Artificial Intelligence? 

The data-rich, complex modern construction environment offers a potential advantage to those businesses that can harness data, produce intelligible insights, and make informed strategic decisions. AI is establishing a footing in the construction industry following years of development and imagination.  

AI is here now because of advances in computing power, algorithms that follow precise steps, the large sets of data the industry produces, and innovations in the systems that combine these advances. The time to understand and integrate AI into your business is now.  

Artificial intelligence is not a new idea, its roots can be traced back to the 1950s. Arthur Samuel, a pioneer in the field, defined it as “the field of study that gives computers the ability to learn without explicitly being programmed.” In other words, AI involves computers and systems that learn from experience. The purpose of AI is to make machines do things that humans are presently doing, but do them better and faster.  

Artificial Intelligence, Machine Learning, and Deep Learning 

Artificial intelligence is a field in data science that blends computer technology with hefty amounts of data to enable problem-solving. You may have experienced AI in a voice search with Amazon’s Alexa or Apple’s Siri. Search engines also power results with AI to collect and retrieve relevant information based on user inquiries. Videos suggested to you by YouTube or Netflix are AI-driven results that recommend titles based on learning your preferences and viewing habits.  

You may hear machine learning mentioned in the same breath as artificial intelligence, but the terms are not entirely interchangeable. Machine learning is a subset of artificial intelligence that learns from experience, adapts, and improves performance without being explicitly programmed.  

A third part of artificial intelligence getting a lot of exposure today is deep learning. All AI aims to mimic human thinking, and deep learning is designed to extract maximum value from our way of processing information. Our brains use what scientists call neural networks, which are the collection of brain cells that help us process information by connecting signals. Deep learning uses artificial neural networks to process large amounts of data and solve problems with limited human help. These artificial intelligence networks are valued for their ability to handle lots of data, continue to improve as it trains and learns, and solve complex issues.   

Artificial Intelligence in Preconstruction 

Before building starts on a commercial construction project, a variety of people and teams from different disciplines and expertise must collaborate and plan how the project will proceed. Preconstruction, as it’s called, refers to the phases of construction that take place before the actual construction work begins. Building owners, architects and engineers, trade contractors, general contractors, building product manufacturers, and many others take part in preconstruction. 

The preconstruction process in commercial construction helps to ensure that the project is completed on time, within budget, and to the client’s satisfaction by identifying and addressing the sequence of people and events that will get the project completed.  

Just like the projects being built, solid foundational work in preconstruction carries over greatly into the strength of the project. Variations in preconstruction stages occur depending on variables such as the type of structure or project (e.g., hotel, school, road, or bridge), project delivery methods, the scope of work involved, or if it is a public or private construction project. 

AI In Preconstruction Project Stages 

The following preconstruction project stages provide a framework for the steps before construction starts and how artificial intelligence is changing how this planning is performed.   

Pre-Design: This phase includes the conceptual design, initial project planning, project development, and feasibility studies. The project team typically begins with the concept of the structure, performs a site analysis to identify potential obstacles, and develops a plan to address them. This phase also includes the development of a rough or working project scope and budget. 

AI in the pre-design or initial project planning and development phase is helpful for feasibility studies to determine if a project is viable. Risks can be identified and analyzed with various data, including financial data, market data, and data on the project’s potential impact on the environment. Risk analysis can assist in deciding whether to proceed with the project. AI is a powerful tool at this stage because it offers thoroughness and accuracy, along with a general lack of bias.   

Design Development: This phase includes the development of detailed design documents that steer the project. Documents included in this stage include architectural, structural, mechanical, electrical, and plumbing plans.  

Design development is a critical phase in the project development process. It involves taking the conceptual design and turning it into a more detailed and buildable design, moving from general ideas to more specific ones. The design development phase is where many important decisions are made that will shape the final project, including cost, energy efficiency, and overall functionality. Artificial Intelligence can play a significant role in this phase by providing new tools and techniques to improve the efficiency and quality of the design development process.  

Construction Documents: This phase includes the development of final construction documents, including detailed construction plans, building product specifications, and contract documents. The finalization of the construction schedule is prepared, which outlines the sequence and expected duration of all activities required to complete the project.  

AI-based tools can be used to automate the process of extracting, analyzing, and processing data from construction documents. For example, natural language processing (NLP) can be used to analyze project requirements and create a detailed project scope document based on two-dimensional construction plans like PDF files. NLP has been around for over a half-century and is the component of AI that understands and interprets human language, written and spoken. This can save time and resources compared to the tedium of traditional methods, such as manual data entry or spreadsheet calculations. 

Bidding and Negotiation: This phase includes distributing the plans to trades, contractors, and manufacturers for bidding. The project team will review the bids, negotiate with contractors, and select winning bids. For general contractors and trade contractors, this is the essential phase that includes producing and delivering detailed takeoffs and estimates to submit a competitive bid.  

Trade contractors, general contractors, and building supply manufacturers assess the project scope, identify opportunities to pursue, analyze bidding strategies, and decide which projects clear the hurdle for success. Trade contractors can use the power of AI to streamline processes, automate repetitive tasks like takeoffs, and improve the speed at which decisions like vetting profitable projects are made.  

Permitting and Approvals: This phase includes the submission of the construction documents to the appropriate governmental agencies, where appropriate, for review and approval. Artificial intelligence is used in this phase to validate building code compliance and manage the building permit process.  

Finalize Preconstruction: This phase includes finalizing contracts, mobilization of the contractors, and the start of construction activities. Effective preconstruction planning and strategic decision-making are key components of profitability for trades, general contractors, and building product manufacturers.  

The finalization of the construction schedule is prepared, which outlines the sequence and expected duration of all activities required to complete the project.  

The preconstruction stages can become more complex due to the nature of the project, the inherent need for effective communication and collaboration among teams, and local and national regulations, among others. Time and budget issues are consistently make-or-break drivers of a profitable construction project. Technology like AI offers an opportunity to improve performance throughout the preconstruction lifecycle.  

Where Else AI and Construction Are Teaming Up 

Aside from preconstruction, AI is a technology continuing to emerge in other areas of construction, enabling improvements in performance and safety. Some examples include:

Predictive maintenance: AI can be used to analyze data from building systems, such as HVAC and electrical systems, to predict when maintenance will be needed and prevent equipment failure

Site safety: AI-powered cameras and sensors (even some worn by workers) can monitor construction sites for potential safety hazards and alert workers and managers to potential dangers. 

Robotics: The efficiency of AI and machine learning have found their way into robotic bricklaying, welding, and even building entire structures with 3D printing.

Project management: AI can optimize the allocation of labor and materials, making the scheduling of construction tasks more efficient and cost-effective.

Quality control: AI-powered cameras and sensors can monitor the quality of construction work, identify defects, and alert workers and managers to issues that need to be addressed.

Building performance: AI could be used to analyze data from building systems to optimize energy efficiency, indoor air quality, and other performance metrics. Simulating building efficiency with AI, for instance, allows the identification of potential energy-depriving areas for better design and construction.  

The Knowledge and Insight Enhancer 

It is common to hear that computers trained to think like humans are a threat to stealing jobs from people. But construction is inherently reliant on the vast institutional and individual knowledge, something that AI cannot replace. Where human judgment is involved, and we know that’s everywhere throughout the construction project lifecycle, AI does not have the capability we humans do.  

It’s more likely that certain roles and responsibilities will change as AI is implemented. AI combined with a company’s organizational knowledge will offer much greater strategic opportunities than those not adopting the technologies to streamline performance and make better data-driven decisions. 

Bright Future for AI in Construction

The present and future of AI in the construction industry are promising as more AI-based tools and techniques become integrated into workflows. As technology advances, AI is expected to become an even more integral part of the construction process, helping to improve efficiency, reduce costs, and enhance construction performance outcomes. AI in the construction industry has landed. Get ready for it.