AI is increasingly helping to accelerate the efficiency of construction projects – empowering more firms to finish ahead of schedule, without the danger of running over budget.
As AI and machine learning (ML) continue to emerge and evolve, more use cases and practical applications in the world of construction are appearing at every step of the construction lifecycle.
According to Fortune Business Insights, the global AI in construction market size is expected to rally from a value of $3.93 billion in 2024 to $22.68 billion by 2032, representing a CAGR of 24.6% over the forecast period.
Already, key industry players have gained access to powerful tools that have the potential to level up productivity throughout the sector.
The Benefits of AI in Construction Management
The prospective benefits of incorporating AI across the construction management landscape are growing clearer as the tools evolve.
Some of the improvements that AI in construction management can bring to firms include:
- Health and safety: AI can be used to predict safety risks by monitoring the durability of jobsite equipment, detecting possible concerns and automating regular maintenance check reminders.
- Planning and design: AI can also enhance project planning with the help of real-time data analysis of historical and current project portfolios, paving the way for more effective decision-making and accurate cost estimates.
- Cost efficiency: Where traditional methods of estimating and monitoring costs can be slow and ineffective at anticipating fluctuating expenses, AI tools offer added precision through predictive analytics to help construction projects stay within budget.
- Greater productivity: One of the leading benefits of AI is automating time-consuming, monotonous and repetitive tasks, leading to improved productivity across every construction phase.
- Quality control: AI can be used to analyze designs, flag potential issues and reduce the dangers of having to rework plans later on in projects.
With a more holistic approach to construction management aided by AI, construction firms can also maximize their energy efficiency and establish more sustainable approaches. This can help construction businesses achieve ESG credentials and remain compliant to regional carbon emissions regulations.
3 Examples of AI in Construction in Action
Use cases for AI in construction management are emerging at a rapid pace, and the following three examples serve as an excellent means of illustrating the far-reaching impact that the technology is having on the industry:
Risk Management
Using AI to effectively anticipate potential safety risks before they occur, based on a blend of ML and real-time analytical insights, is one of the most valuable means of utilizing the technology in construction management.
Leveraging data across different sources, including project plans, worker profiles, and historical incident reports, means that managers have more insights at their disposal to implement preventative measures and lower the risk of workplace accidents.
Platforms like Access Coins ERP are an example of AI-powered construction software that firms can utilize across multiple sites. By connecting office and field teams through cloud-based systems with remote access, compliance challenges can be navigated effectively.
By using comprehensive forecasting tools, construction Enterprise Resource Planning (ERP) software allows businesses to predict and navigate potential risks not only in terms of safety but in prospective labor or materials shortages, anticipating issues long before they have a chance to disrupt operational efficiency.
Scheduling Efficiency
Construction project scheduling is a complex process that requires significant attention to detail to track dozens of moving parts.
Project managers generally turn to these schedules for progress control, cross-checking ongoing progress against forecasts. However, construction management can also face unexpected challenges that can impact scheduling at scale – leading to a domino effect that can eventually lead to delays, rework, and budget overruns.
AI-powered schedulers have become increasingly commonplace due to their ability to analyze a multitude of interdependencies and data sources required for the completion of projects.
With the help of AI, project management tools can determine the optimal resources for each project stage, while the technology’s ability to rapidly interpret swathes of big data and unstructured information sources helps to shape powerful (and actionable) insights.
An example of this can be found in Ananda Development’s use of an AI scheduler developed by ALICE Technologies to support a high-rise project in Bangkok, Thailand.
The solution ran different scheduling scenarios to determine the most effective path, helping the company to keep its project cost and duration considerably lower than manual scheduling methods, reducing the total time spent delivering the project by 208 days.
Quality Control
AI is also transforming quality control processes at construction companies. In one notable instance, China State Construction opted to use AI in their construction project management to control quality in real-time, helping to improve construction standards and actively lower instances when rework is required.
With the help of AI-powered cameras and building sensors, construction firms were able to utilize real-time detection of design specification deviations throughout the construction process. The deployment of the technology helped to lower instances of rework by 18%, with overall construction quality management improving as a result.
Given that rework can be an expensive process, AI quality control tools are helping more construction firms lower costs and improve their reputation as a company that can adhere to strenuous guidelines without exceeding timeframes.
Embracing AI in Construction
AI is set to play an essential role in improving the cost-effectiveness and overall efficiency of construction management at scale.
The ability to maintain a higher level of accuracy and a more comprehensive degree of safety without running the risk of compromising on agreed timeframes or budgets means that more construction firms can benefit from AI throughout day-to-day operations.
The arrival of AI could be revolutionary for construction. In an industry where cost-saving while caring for worker safety is imperative, the adoption of AI should be a key consideration for all firms.
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