Construction bottlenecks are a persistent problem throughout the industry.
Driven by the fact that construction projects rely on many different parts working in sync, any small delay or misstep can result in a severe progress block. These blocks drive back time frames and operational costs, making them one of the biggest risks in construction.
To combat this, many companies are turning to software and platforms that offer assistance in managing their construction projects. As technology has advanced in recent years, an increasing number of these platforms are offering integrated AI to boost their service and capabilities further.
But, even with the prevalence and push for AI, many managers are still unsure how useful AI really is, and because of this, are hesitant to start using it in meaningful ways. To understand just what AI is capable of when it comes to construction management, it is important to understand why bottlenecks are still happening first.
What Construction Bottlenecks Are
Bottlenecks are often the result of operational weaknesses, rather than technical failures.
Delayed or limited communication causes bottlenecks as teams wait for the information they need before they can continue to the next duty. Poor communication also leads to delayed decision-making, furthering wait times.
Manual data entry and a reliance on other outdated processes slow down entire teams as they work to fulfil an obligation that could be done another way. Delaying them from more productive work and halting progress.
Lack of project visibility and resource misallocation can result in bottlenecks, as too few people try to do too much, or complex tasks are completed without the tools needed. This can cause progression to drag much longer than expected.
So how can AI help?
Where AI Can Help
Data Analysis & Pattern Recognition
When given the correct data, AI is able to help identify trends emerging within a project. This allows management to stay on track and make adjustments as needed much more easily.
It is also helpful to spot inefficiencies as a project progresses to help managers reallocate resources that might make a huge difference elsewhere. This helps boost their flexibility and supports their team more easily and with more accuracy.
Early Risk Identification
AI, when given the correct parameters and information, is able to help managers predict high-risk portions of the project as well as forecast what will cause the problem. This helps managers act proactively and save time and money further on in a project.
It also helps them on an ongoing basis by reacting to new data and using the earlier details to check for developing issues and potential risks to help the management team prepare. This extra clarity gives management confidence in their direction.
Reducing Manual Admin
Using AI to help with data entry and report creation can help remove some of the more mundane and repetitive aspects of the procedure. It can also help highlight potential issues as well as missing data that can help keep things comprehensive.
Reducing the amount of repetitive tasks means that your team will need to spend less time on formal processes that slow down their progress. Having a system double-check for missing information helps reduce their cognitive load, lowering the chance of errors and the need for double-checking.
Overall, AI is most helpful when it is assisting your team in finding patterns and using the information to remove friction from their daily work. However, AI still has some limits.
Limitations of AI
Poor Workflows
AI will function based on the information that it is given. It might even be able to suggest ways to better use it, but it will still require input and a basis from the company itself. If a project is stopping due to a process that cannot be bypassed or removed, AI cannot help.
This means that if there is an issue with the way data is collected and processed within the company, this will be reflected in any suggestions or ideas given by the system.
Communication Issues
AI can still lack nuance in the way it communicates. It can also struggle when it isn’t given the full context of the task it is given. This means that in bottlenecks that require precise communication and explanations, AI may not be able to assist fully.
Relying on AI without using human alignment can lead to solutions that don’t quite work or aren’t suitable.
On-Site Constraints
AI can help behind the scenes, in organization and data processing. However, it is limited to computers and phones and cannot affect things in the field. In-field bottlenecks will still need to be dealt with by the team there.
This means that although it can give suggestions, it is unable to physically help the team when it comes to on-site work.
AI can assist, but it cannot solve human-based issues, like short staffing or structural issues within a company.
The Reality of AI in Construction Management
AI has developed rapidly, but it remains most suitable as a support tool to enhance the way your team works. It can help develop project management by streamlining certain processes & can help condense data into actionable suggestions and warnings, which are all valuable as costs get higher and margins get tighter.
But AI cannot replace the people within a business. It will still require both input and consideration from the staff who use it. It will also need to be used alongside well-organized processes and comprehensive data in order to be effective.
When it comes to addressing bottlenecks in construction management, AI can directly help boost visibility and provide tailored suggestions to both reduce the chance of bottlenecks and provide actionable suggestions when they happen.
But the most effective approach is for companies to combine AI insight with strong operational practices, combining the strongest aspects of both.