On 30 October 2024, K2 Integrity hosted a webinar focused on the integration of AI in construction, outlining practical applications, implementation considerations, and future trends. The conversation included Bradley Sussman, senior managing director, construction and real estate risk management at K2 Integrity; Christopher Ward, associate managing director, construction and real estate risk management at K2 Integrity; and DeShon Clark, chief AI officer at Allventa. Click here to view a recording of the session.
Artificial intelligence (AI) offers significant opportunities for the construction industry, particularly in automating repetitive tasks, improving safety, and managing complex workflows such as identifying invoice anomalies and optimizing schedules to enhancing safety with predictive maintenance. As AI adoption grows, it remains critical for companies to address data management, regulatory compliance, and ethical considerations. A clear AI strategy can help companies leverage AI effectively while aligning with industry regulations and ethical practices.
AI Integration in Construction
There are five levels of AI integration. Level one is at the individual level where you start to tackle prompt engineering. Level two is at the organizational level where there is a plan to upskill the organization. Level three infuses AI within applications. In level four, AI operates with little human monitoring or intervention. Level five occurs when there is full trust in the AI, and the resulting impact is monumental.
While the level of AI integration varies across organizations in the construction industry, the technology is already having an impact on the industry in a variety of ways:
- Process Optimization and Efficiency: AI-driven applications are becoming instrumental in automating tasks and optimizing resources across construction projects. Construction teams face high costs and time constraints, and AI can streamline administrative and operational workflows by:
- Automating repetitive tasks such as paperwork submission and resource scheduling.
- Analyzing project timelines to identify potential delays and resource shortages.
- Generating reports, proposals, and contracts faster and more accurately.
By leveraging tools like Microsoft’s Power Platform, companies can automate workflows, manage data, and enhance collaborative efforts, saving critical hours and resources.
- Safety Enhancement and Risk Mitigation: Safety is paramount on construction sites, and AI has proven to be a valuable tool in mitigating risks and maintaining compliance with safety regulations. AI-enhanced safety applications include:
- Real-Time Monitoring: AI models analyze live camera feeds to ensure workers wear appropriate personal protective equipment (PPE), such as hard hats. If a worker’s PPE is removed, AI flags this in real time for rapid response.
- RFID Tracking: RFID data can be used to track worker movement patterns to monitor job-site attendance, detect trends, and alert site managers to potential safety hazards.
- Predictive Maintenance: Using historical equipment performance data, AI can anticipate machine failures and suggest proactive maintenance, reducing the risk of accidents and project delays.
By implementing these safety-enhancing applications, companies can reduce the frequency and severity of accidents on construction sites, ensuring that all workers return home safely.
Implementation Challenges and Solutions
A common challenge to implementation is that data relevant to AI applications is often spread across multiple systems, making it difficult for AI models to access and process the information. Addressing this issue requires establishing a unified data platform, such as Microsoft Fabric, to consolidate data sources; implementing AI frameworks that cleanse and structure data, enhancing its utility for predictive and analytical purposes; and training models with proprietary company data to ensure AI outputs are tailored and relevant to specific project requirements.
Another challenge is that AI’s rapid advancement outpaces regulatory frameworks, creating potential compliance gaps for companies. To address these potential gaps, organizations should:
- Implement an AI governance framework, including protocols for data privacy and transparency as well as usage guidelines.
- Establish ethical AI councils or working groups to ensure AI practices align with industry standards and regulatory compliance.
Future Trends in AI for Construction
The future of AI in construction may include fully autonomous AI agents capable of managing specific regulatory or safety functions. As AI technology evolves, the construction industry could employ “AI co-workers” for tasks requiring high accuracy and speed, minimizing the need for human intervention.
Small language models, designed to handle specialized tasks, will become essential for ensuring accurate compliance with construction regulations and ethical standards. These focused models can act as gatekeepers, ensuring AI outputs align with specific industry guidelines and reducing the risk of biased or noncompliant decisions.
AI systems trained with both external and proprietary data to create custom models will enhance construction efficiency, though companies must proactively address regulatory changes. By establishing data governance structures and implementing real-time compliance checks, organizations can safely advance their AI initiatives.
AI presents a substantial opportunity for construction companies to improve efficiency, safety, and project management. While adoption remains in its early stages, organizations with a clear AI strategy and robust governance framework are best positioned to capitalize on AI advancements. By addressing AI’s capabilities and challenges, companies can effectively integrate AI to enhance operational outcomes and establish a sustainable, compliant AI framework.
