Large construction projects take 20% longer to finish than initially scheduled and are up to 80% over budget. That’s more guesswork than one could imagine.
Construction companies often remain uncertain about the advancements in construction technology, AI, and its potential for cost reduction. As a result, they encounter three pain points:
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Budget overruns
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Delayed project timelines
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Misallocation of resources
Most of these enterprises have barely scratched the surface when it comes to experimenting with AI systems for workflow optimization. Unfamiliar with the AI capabilities, many choose to abandon the process midway.
This misinterpretation leads to missed opportunities and a lack of recognition for AI development services that could have optimised workflows from the get-go.
Still unsure how AI can help cut operational costs and get your project deadline on track? You’re at the right place. In this blog, we’ll walk through the practical use cases of artificial intelligence in construction projects.
How AI in Construction is Reducing Cost and Time for Large-Scale Projects?
One might think, artificial intelligence in construction? Sounds unusual, but the potential of AI tools is overlooked in the construction industry. To debunk this myth, let's examine how AI-based solutions for businesses save money and time:
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Machine Learning Models
Machine learning models are like independent, self-improving bots. They learn from data patterns and make predictions without any explicit programming. This continuous learning curve results in iteration and accurate cost estimates.
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Predictive Analytics
AI services analyze and foresee potential risks and delays in advance, allowing you to reroute your project plan onto a safer path. Predictive analytics is also instrumental in resource allocation, budget optimization, and risk mitigation.
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Autonomous Project Management
Project schedules need constant realignment with a nagger who won’t leave your side until you finish the designated task. AI tools can adjust project schedules in real-time, eliminating the manual hustle and ensuring all team members are well aware of their responsibilities.
Forward-thinking enterprises are eager to build advanced AI software that can instantly streamline their project workflows.
Where to Use AI Applications in Your Project Timeline?
Looking for smart and effortless ways to integrate AI systems in your workflow? Check out these key areas where using AI for construction projects is a must:
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In Project Management
Project delay leads to budget overruns; it's a vicious cycle. A solution to stay on track is AI-powered project management tools. These systems assist construction professionals in:
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Creating routine schedules to optimize the project timeline
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Predicting unforeseen events to realign tasks
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Providing insights on project milestones and supply chain disruptions
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In Resource Planning
According to reports, resource wastage in construction projects ranges between 20% and 30%. That’s a lot, right? This is where AI-based solutions are deployed to analyse current and historical project data. Ultimately, leading to:
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Management of project resources concerning the project scope
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Assignment of tasks based on workforce skillsets, ensuring the right task is aligned with the right worker
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Accurate track records of equipment usage to reduce downtime
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In Project Design and Architecture
Sometimes architectural designs are not feasible, and even if they are, you can’t say for sure whether these ‘imaginative designs’ will meet your client deadlines. The best use case of AI models here is to:
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Optimize design for efficiency, sustainability, and cost savings
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Facilitate round-the-clock inventory and waste management
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Bridge the gap between client expectations and project deadlines
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In Predictive Management
Unanticipated machinery failures result in project obstructions. These unforeseen events can be a costly gamble. AI systems eliminate these disruptions by:
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Notifying project managers in real-time to avoid last-minute quick fixes
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Detecting malfunctions in equipment to prevent downtime
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Scanning the construction site to monitor progress
Common Challenges Construction Companies Face During AI-Integration (With Solutions)
Jumping right into AI integration without resolving its pitfalls can be a risky call. Here’s a list of challenges you should address before using AI for construction projects.
Challenge 1: Lack of Human Expertise
AI models are as capable as the professionals working with them. To leverage and refine an advanced AI software, on-site engineers need expertise in predictive analytics and machine learning models.
Solution: Partner with AI Experts
If you are unsure where to start the process of AI integration. Whether to hire data scientists or consult with custom AI development companies. The ideal choice here would be to hire skilled AI developers who can optimize your project workflows from day one.
Challenge 2: Unavailability of Quality Datasets
Artificial intelligence systems are heavily dependent on quality datasets to create effective project strategies. One repetitive issue with construction companies is inaccurate data, which leads to inaccurate results.
Solution: Prioritize Data Quality
Before you get all pumped up to work the wonders of AI models, check for quality datasets first. You don’t want your AI-integration plan to backfire before it gives efficient results.
Challenge 3: Business Ethics and Privacy Issues
AI models can violate ethical practices just to complete the project on time and within budget. When working with AI systems, ensure that the project roadmap doesn’t violate workers’ privacy.
Solution: Build Compliance-Friendly Strategies
Non-compliance with regulations leads to unwanted penalties and interventions. Automated systems help in streamlining documentation to minimize manual errors. Use IoT sensors to track noise levels, A5 emissions, and waste management.
Challenge 4: Contextual Complexity
Working with AI in mega construction projects is a complex task; there is a chance that these systems may not be fully prepared to act on the nuances involved.
Say you want a site-specific project plan that accounts for topography and complies with local regulations. The AI model may fall short in shaping a detailed project plan and tend to generate vague responses due to the unavailability of niche information.
Solution: Integrate Geospatial AI
GeoAI combines machine learning and deep learning models to analyse geospatial data.
These applications can accelerate real-world understanding of business operations by automating the extraction, classification, and detection of information from multiple data sources such as imagery, video, point clouds, and text.
In a Nutshell
AI in mega construction projects is no longer a buzzword. It has real-world applications in the construction industry. Whether it’s resource allocation or project design and construction, AI is ready to transform operations.
Caterpillar, for example, makes the most of AI and IoT in their construction machinery for predictive maintenance and operational efficiency. Their AI system collects data from equipment to reduce downtime and increase longevity.
Want to be the next big construction company to leverage AI in their projects? Infutrix is here to help with our custom AI development services for every domain. Let’s revolutionize your projects to maximize cost savings.
