Harnessing the Power of AI in Construction

Artificial intelligence (AI) can change how construction projects are done, freeing up time and space for the most important parts of a job by streamlining several steps in the build. Unlocking AI’s potential in construction requires knowing how to use it, how to identify its limitations, and how to introduce it to the people doing the work it's meant to enhance. 

This article explores AI in construction, including deployment strategies, best use cases, common challenges and best practices for using it effectively. 

Defining AI in Construction

Most of the things currently referred to as “AI” in construction are technically artificial narrow intelligence (ANI). ANI relies on structured systems designed and trained to perform a specific task or set of tasks. Everyday examples include map apps that suggest routes based on real-time traffic, email inboxes that filter out spam or ChatGPT and other large language models (LLMs) that have been designed to understand and generate human language. 

Building a tech stack of tools to help efficiently use AI for data acquisition streamlines workflows that are already common in effective project management, such as project schedules, material inventories or safety inspections. 

First Steps to Implementing Construction AI

The success of innovation in construction isn’t defined by how popular it is, how advanced the tech is or how much it promises to revolutionize the jobsite. An effective innovation in construction can be any tool, method or habit that solves a problem, optimizes the construction process or improves final outcomes. AI is no different. Harnessing AI’s power starts with understanding a problem that needs to be solved or identifying an end goal and assessing whether AI is the best solution to get there. 

Training the Technology

AI usually promises increased efficiency, but only when it is applied as a tool for solving specific problems and achieving ideal outcomes. With generative AI, the requirements for building effective AI systems have changed significantly. This new form of AI allows for the creation of multiple “AI experts” who can handle unstructured information and data in a way similar to human operation. 

Unlike traditional machines, people have the ability to fill in gaps using their various specialties, and generative AI can now mimic this capability. By leveraging generative AI, the boundaries of technology is pushed to achieve things that were never possible before.

5 Key Applications of AI in Construction

The uses for AI are vast and expanding all the time. AI can be deployed across various areas of an organization and programmed to collaborate with other AIs to address challenges that arise on projects, including procurement, risk mitigation and coordinating work.

1. Material Procurement

Material management and value engineering has historically required someone to spend hours and hours on locating required items, finding the best price and determining when they can be delivered. AI can help automate much of the takeoff process, including analyzing digital plans and quickly generating lists of material quantities and cost estimates. AI can also help with comparing numerous options for a component and recommending vendors that are more likely to be able to provide it in an ideal timeline. 

2. Optimizing Team Performance

Most contractors work hard to decide how to build and schedule teams that are ideal for a given project. AI is able to analyze data and provide recommendations around assembling and scheduling the ideal team for any given project or phase or a project. This process might include assessing workers’ certifications, analyzing past performance, and comparing efficiency with different partners. 

3. Accurate Financial Forecasting and Monitoring

AI can analyze spending trends and historical data to provide more accurate forecasts. Digital tools can help visualize current spending, compare it to projections and recommend improvements based on past projects. This type of real-time financial monitoring can help identify trends or financial blindspots.

4. Risk Management

AI is able to analyze historical projects and data about claims to dramatically improve the processes of risk assessment and applying for sureties. Data can help inform decisions about accepting or bidding on new projects, and analytics can help identify potential risks and take preventative measures, which can lead to a reduced number of claims and possibly lower insurance rates. 

5. Identifying Potential Safety Hazards

Safety AIs are trained in construction management, safety science, and various reference materials. In some cases, they can even be trained on local building codes.

How to Overcome Common Construction AI Challenges

Address resistance with open communication.

People can be resistant when they’re being forced to implement tools they don’t understand, don’t see the use in or fear could put them out of work. Taking time to listen to people’s concerns, address them directly and explain why a new innovation is being adopted are often the best ways to get people invested. Further, the people with these concerns are also those with the most expertise. Making space to talk openly can enlist that expertise in finding ways to maximize AI’s impact.

Cultivate shared values and collaborative opportunities.

Team culture built on values such as open communication, safety and the pursuit of excellent outcomes for clients moves the focus from people’s fears about AI towards its potential as a tool. Similarly, having a culture that values experimentation and doesn’t penalize failure can help people feel more open to trying new innovations. 

To help foster collaboration around AI, contractors can create internal focus groups that allow team members to give feedback and suggestions on what information to feed AI. 

Be consistent with data.

A significant challenge in the construction industry is the amount of fragmented data collected from projects. Because operations are generally decentralized, both employees and AI have to be trained on how to gather the right data and streamline the process across projects. 

Build trust.

It’s hard to trust what we don’t understand. Many people don’t know how AI works or how it can complement their work. Building trust often starts with training people on how systems work, including information on its limitations. 

While AI can seem intimidating, it’s important to understand that AI introduces new complexities, but doesn’t necessarily make everything easier, or mean employees lose jobs. By managing the increased complexity AI brings and ensuring people are properly equipped with AI tools, employees and contractors will remain essential to the work being done on jobsites. 

Benefitting From AI in Construction

In the long run, the people working in construction that will benefit the most from AI aren’t necessarily the most tech-savvy. They are the people who value continuous improvement, seek ways to improve what they do and are open to new ways of thinking. Effectively implementing AI is similar to effective project management: it requires identifying problems, coming up with solutions and being open to ways to improve. 

For all AI is already doing, its future is still largely unwritten. Being part of the process of embracing, creating and giving feedback on AI innovations increases the likelihood that the future will be one where technology is a tool that benefits people and helps them spend more time on the most important and rewarding parts of their job.

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