AI and the Construction Life Cycle: What Can We Expect to Change?

The construction life cycle is a complex process, from the initial conceptualization to the final building and closing. Professionals in the industry dedicate hours every day to tasks like planning, project management, procurement, scheduling, and quality control – all of which require detailed attention and coordination.

Naturally, this process isn’t without frequent snags, ranging from design flaws to logistics delays to weather-related problems. These challenges have long been accepted as part of the construction landscape – they just happen.

At least, that’s how it used to be.

With the dawn of Artificial Intelligence (AI), the industry stands on the cusp of a lasting transformation. AI promises to revolutionize the way we conceive, plan, execute, and track construction projects, making the construction life cycle more efficient than ever.

In the coming years, here are the big changes the industry will likely see due to the rise of artificial intelligence tools.

Improved Communication and Transparency

Successful construction projects require clear and efficient communication – and there’s a lot on the line. Unfortunately, communication is not the strong suit of most construction teams.

Communication mistakes frequently result in costly delays and disruptions and missed deadlines, many of which could be avoided with more reliable communication. Moreover, important stakeholders expect (but often fail to receive) continuous updates on project progress, insights, and results.

That’s a key area where AI offers a solution.

Advancements in AI technology will lighten the load on project managers and significantly streamline the process. With software like this, construction teams will be able to perform time-consuming and detail-oriented tasks in record time. They can also gather, analyze, summarize, and share crucial data, so everyone (including stakeholders) is updated.

Through new AI construction technologies, seamlessly getting information where it needs to go will enhance communication and allow for more real-time analysis. Workers, project managers, and stakeholders are automatically notified and updated on important changes, reducing frustration, miscommunication, and project disruptions.

Meaningful Data Management

One of AI’s greatest achievements is its ability to rapidly organize data. It can process complicated data analysis in seconds, freeing up time that was formerly spent on manual tracking by managers and workers.

In the construction industry, disciplined organization of data is crucial. There are many areas that require daily attention, such as the management of cost, tracking progress, material and resource utilization data, and scheduling data.

AI construction tools will have the ability to gather, connect, and analyze data in these categories quickly and easily. In an instant, AI can provide valuable insights that might have otherwise been missed while saving the construction management team hours of time (if not days).

Artificial intelligence can also identify holes and inefficiencies that are difficult to connect. The more construction companies are aware of these “holes,” the easier it is to plug them – before money or time is lost unnecessarily.

Furthermore, AI analyzes vast amounts of data. It's also able to generate highly specific, beneficial recommendations on everything from logistical issues to pricing.

According to a 2021 study, AI tools in construction can act as a proactive “co-pilot.” General recommendations are often reactive and based on established standards. However, AI's proactive suggestions stem from real-time data analysis and predictive modeling. These tools can foresee potential issues and suggest best practices in advance.

Facilitating Connections Between Software

As it stands, the construction life cycle presents challenges to project managers and employees – namely, the scattered project data found across many different pieces of software.

The initiation, planning, implementation, monitoring, and closing phases of projects often involve their own specialized software and separate software for each function within each phase. For example, software used for design, payroll, planning, forecasting, change management, cost management, scheduling, procurement, and more. Typically, the software operates in silos, making data sharing and collaboration across platforms challenging.

Because these processes are all interconnected, they need to work together. If they don’t, it can lead to serious (expensive) issues down the line. For example, when specific trades are in high demand within a certain region due to the number of similar projects that are underway at the same time, this can have major consequences for one or all of those construction projects.

AI prevents issues like this from happening. It uses advanced integration tools, providing a unified, accessible, and actionable view of the project and the conditions in the region that may impact the project.

From a design perspective, AI can also assist with the logistics of how to implement the construction. For instance, using data from various software tools, it can calculate how much space is needed to ensure safety during the construction process and avoid conflict.

More Efficient Scheduling

Scheduling is one of the biggest day-to-day complications in the construction life cycle. This is largely due to the number of interconnected tasks, dependencies, and stakeholders involved. Delays in one task have cascading effects on the entire project.

Using machine learning, AI construction tools strengthen with each use and continuously improve scheduling efficiency, decreasing the number of project delays.

AI can coordinate logistics and streamline scheduling in several ways. For one, by assessing historical data and trends, it can predict potential scheduling conflicts, making the process efficient and frustration-free.

It can also automate and optimize resource allocation, reducing idle time. Moreover, AI can enhance logistics by minimizing double handling and storage needs.

AI-powered predictive maintenance systems are transforming asset management by using machine learning algorithms to predict potential breakdowns before they occur. This enables timely maintenance and reduces costly repairs and down time. It also extends the lifespan of equipment by optimizing proper utilization.

By leveraging machine learning algorithms, construction companies can better …

  • Predict equipment failures
  • Schedule maintenance activities
  • Optimize maintenance schedules within the changing environment of the project schedule

This proactive approach minimizes downtime, improves equipment usability, and reduces costs associated with delays caused by reactive maintenance.

Easily Track Project Progress

AI is incredible when it comes to providing in-depth analysis of an individual project’s progress. Additionally, it’s able to accurately track construction quantities. This prevents common discrepancies between what is being done in the field and what is being reported on time progress sheets, which improves productivity tracking.

AI tools can also dramatically enhance quality control in construction. With its analyzing capabilities, it can pinpoint potential problem areas before they escalate and predict structural deficiencies or safety hazards. Automated drones or AI-enabled cameras can also inspect sites more frequently, identifying and tracking issues humans might miss.

These capabilities all allow for AI to be a powerful tool to assist with management tasks, reducing idle times and turning projects into a source of data for future improvement.

Better Connections with Suppliers

Artificial intelligence software’s ability to enhance the connections between construction teams and suppliers is a growing topic of interest.

AI can analyze vast amounts of data to match construction teams with the most suitable suppliers based on factors like material specifications, quality, proximity, and delivery times. This ensures that the right materials are available when needed.

Furthermore, AI provided valuable insights into cost management. By processing pricing data, it can predict future price trends, allowing construction teams to source materials at the best possible price. This makes the process of outsourcing supplies vastly more efficient, requiring far less human labor.

The Wrap-Up

The construction industry is at a pivotal point in history. Soon, with the utilization of AI technology, companies will be able to streamline the construction life cycle, dramatically minimizing common problems within the industry.

Ultimately, it’s clear that companies willing to embrace these new technologies will be ahead of the curve. By including AI as an essential tool in their arsenal, they’ll be positioned for success in an ever-evolving industry.

About the Author

George Goubran is CEO of Built On Vision. For more than 25 years, George has provided valuable insight and leadership to companies and boards seeking to develop new products, scale business, drive organic growth, and turn around underperforming segments. His record of success includes founding, scaling, and leading technology, Software, SaaS, and Cloud companies to market segment domination, profitability, and successful product acquisition. He has the analytical expertise and business foresight to determine and seize market gaps ripe for disruptive technology solutions.

Following his success in these spaces, he sought out and brokered deals with potential partners to expand into the oil/gas, aerospace, and engineering industries. This resulted in his launch of Built On Vision (BOV), a multiple award-winning critical path method (CPM) forensics software built on an in-house designed AI. In 2019, BOV went international with a software update to automatically translate schedules into any language. Since its release, the software has made the 2019 Red Herring Top Product list and has been integral to the smooth-running of $20B+ in construction and infrastructure projects.


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