Practical opportunities for AI in construction
Hello colleagues! I have been working in the world of architecture and construction for decades, I have seen trends come and go. However, the hype surrounding artificial intelligence (AI) is different. It's not just another buzzword; a technological leap that can fundamentally transform how we design, build and manage projects. I know that as a manager or project manager of an SME, your time is expensive, and it is difficult to deal with the great technological achievements of the future in addition to everyday firefighting.
This guide is for construction SMEs that want to start using AI through a clearly defined task and a manageable investment.
Why should an SME deal with AI at all?
Before we get to the "how", let's clarify the "why". AI is not a technology for its own sake. It can bring concrete business benefits, even on a smaller scale (as highlighted by industry analyzes [2]):
Efficiency increase: Automation of repetitive administrative tasks, faster data analysis.
Cost reduction: More accurate cost estimates, minimizing waste, early detection of risks (e.g. predicting delays, cost overruns).
Better Decision Making: Data-based insights on project status, optimization of resource allocation.
Quality improvement and Security: Recognizing patterns in errors, identifying potential security risks based on data.
Competitiveness: Companies that are open to new technologies can gain a long-term advantage.
Where Do We Start? The First Realistic Steps
The most important advice: don't want everything at once! Forget the self-thinking robots of Hollywood movies. Let's start small, where the pain is greatest or victory is easiest.
Identify the Key Problem: Where are we wasting the most time or money? With schedules constantly slipping? With inaccurate cost estimates? With a lot of paperwork? Choose one specific area where you want to improve.
Let's Look Around Among Our Existing Tools: A surprising amount of modern software already has built-in, "unnoticeable" AI functions. Do we already use any project management, budgeting or even communication platforms? It's worth checking if they offer AI-based assistance.
Let's start with Data: The "fuel" of AI is data. Even if we don't immediately introduce AI software, let's start consciously collecting and organizing the data of our projects in digital form. This is a valuable step in itself. The importance of data-driven operation is emphasized by many studies [3].
What Data Do We Need?
Let's start with what we already have and strive for quality:
Project Basic Data: Duration (planned vs. real), costs (planned vs. real), resources (people, machines).
Communication and Documentation: E-mails, minutes, design versions, RFIs (requests for information), change requests.
Field Data (if available): Daily reports, photos, drone footage (these are analyzed by more advanced AI).
Safety Data: Incidents, near misses, inspections.
The most important thing: the data should be digital, structured (as much as possible) and accurate. AI cannot draw good conclusions from bad data either. Digitizing and standardizing data collection processes is a huge step!
Addressing the Challenges: Cost, Data, Expertise
Let's be honest, the introduction of AI does not go smoothly. But the challenges (addressed in industry reports) are manageable:
Cost:
Solution: Let's start with low-cost or free (freemium) SaaS (Software as a Service) solutions. Let's focus on the areas that promise a quick return (ROI). Running a pilot project in a single area means less risk. Don't buy expensive software until you know exactly what you're going to use it for.
Data (Quality and Quantity):
Solution: Let's start digital data collection now! Invest in data quality - it will pay off in the long run. We don't need "big data" right away, let's start with the most important existing data. Perhaps the first step is to implement a better data management system, not directly that of an AI tool.
Lack of expertise:
Solution: Look for user-friendly tools that do not require programming skills. We train existing employees to use specific software. In many cases, AI does not replace, but complements and strengthens existing expertise (e.g. in the hands of an experienced project manager, AI data is even more valuable). If necessary, an external consultant can help with the first steps and strategy creation, but the goal is to build internal knowledge.
Resistance to Change:
Solution: Let's clearly communicate the benefits (not the loss of jobs, but easier, more efficient work). Involve the team in the selection and onboarding process. A successful pilot project is more convincing than any presentation.
AI Is Not Magic, It's a Tool
Just like a good plan or a reliable machine, artificial intelligence can be a tool in our hands. For construction SMEs, the key is not chasing the latest, most expensive technology, but a gradual, thoughtful introduction that solves specific problems and creates real value. Let's start small, focus on data, and choose tools that support our existing processes and expertise.
Toldy Construct is committed to quality and efficiency, and we believe that technological advances, including AI, can help take these values to even higher levels. AI is not a distant promise of the future - we can take the first steps towards it today.
How to proceed?
Think about it: Which is the one area in the company's operation where there is the greatest need to increase efficiency or reduce errors?
Check: Are you already using software that may have hidden AI capabilities? What do the SME-friendly project management or data analysis tools available on the market offer?
Talk to your team: How do they see the possibilities of technological development? Where do they feel the greatest need for help?
Digital transformation is a journey, not a single leap. Let's go about it judiciously and use AI for what it is meant for: to build better, smarter and more efficiently.
Source:
McKinsey & Company: "AI in construction: Paving the way for a smarter future" (October 18, 2023) - Comprehensive article on the potential of AI in construction, including the impact on SMEs. https://www.mckinsey.com/capabilities/operations/our-insights/ai-in-construction-paving-the-way-for-a-smarter-future (Accessed 28 May 2024)
Deloitte: "Future of Construction: Building a digital tomorrow" - Although this is a more general report on digitization, it emphasizes the importance of data-driven decision-making in the industry. https://www2.deloitte.com/xe/en/insights/industry/engineering-and-construction/future-of-construction-industry.html (Accessed 28 May 2024)
Associated Builders and Contractors (ABC): "Tech Report: Overcoming Challenges to Technology Adoption" (2023) - Although American-focused, it identifies relevant challenges (e.g. cost, training, integration) related to technology adoption in the construction industry. https://www.abc.org/Portals/1/CE/Docs/2023%20Tech%20Report%20FINAL.pdf (Accessed 28 May 2024)
Sources
https://www.abc.org/Portals/1/CE/Docs/2023%20Tech%20Report%20FINAL.pdf
