How AI is Transforming Construction: Challenges, Opportunities, and the Future of Contract Automation
Over the past decade, AI has been revolutionising industries across the board – but construction has been slow to adapt. While other sectors are reaping the benefits of automation and advanced data analysis, the construction industry currently lags behind in adopting AI, despite huge potential to transform processes.
A recent scoping review from the Norwegian University of Science and Technology of 86 peer-reviewed articles from 2015 to 2020 highlights both the challenges holding back adoption and the opportunities AI presents. The report was published back in 2022, but have things changed that much in the industry since then? In this blog, we explore these findings and examine how AI could also enhance contract management in construction.
The State of AI in Construction
Construction is a vital but complex industry, contributing significantly to global GDP while being notorious for inefficiencies, fine margins, and delays. The recent LSE Construction Adjudication Report summarises this, with the number of projects leading to disputes increasing 9% on last year alone.
While AI in construction is something that has received some consideration over the past decade, most research focuses on specific tasks like cost estimation, scheduling, and safety planning. Machine learning models can predict costs and optimise schedules, while AI-powered tools enhance safety by identifying hazards and monitoring sites. However, the majority of AI innovations in the industry remain in the testing phase, with limited large-scale implementation.
The Potential of AI in Boosting Productivity
Despite the slow uptake, AI holds huge promise for the construction sector. Much like it has done in other fields, one of the simplest and most immediate benefits is the potential to free up human workers to focus on higher-value activities, such as strategic planning and problem-solving. But it’s AI’s integration into software that provide some real boosts to project teams, with its ability process vast amounts of data to provide actionable insights for better decision-making at a quicker rate. For example:
- Cost and Schedule Management: AI tools can analyse historical project data to improve cost estimates and create more realistic schedules, reducing overruns.
- Resource Optimisation: AI can ensure that materials and equipment are used efficiently, minimising waste and cutting costs.
- Safety Enhancements: AI-powered cameras and sensors can monitor construction sites in real time, flagging potential safety issues before accidents happen.
- Risk Assessment: Advanced algorithms can predict project risks based on historical data, allowing managers to proactively address potential problems.
How AI Can Revolutionise Contract Management
Construction contract management is a critical area that is already seeing the benefits of AI. Contracts in construction are often highly complex, involving multiple stakeholders and detailed terms. AI can bring automation, efficiency, and accuracy to this process in several ways:
- Automating Contract Creation: AI tools can quickly help select the best form of contract for a particular project, generate standardised contracts, reducing administrative workload, minimising human error, and ensuring compliance with industry standards.
- Risk Identification and Management: Automation enhances risk analysis by identifying problematic clauses or areas in contracts that could lead to disputes, delays, or compliance issues. This allows project teams to proactively address risks early.
- Real-Time Monitoring and Insights: AI-powered systems provide real-time updates on contract milestones, ensuring stakeholders are notified of deadlines, payment schedules, or potential breaches, thereby reducing delays.
- Streamlining Approval Workflows: Automating the approval process for contracts and change orders ensures a seamless flow between teams, saving time and preventing bottlenecks.
For construction companies looking to streamline their operations, adopting AI in contract management is a practical step forward. Tools like those highlighted in the Built Intelligence Contract Automation Playbook showcase how AI can revolutionise this critical area, making it easier to manage complex projects and improve outcomes.
AI We Are Currently Adopting
At Built Intelligence, we are already harnessing AI to transform project delivery. Our Contract IQ platform is designed specifically for project teams, offering highly accurate AI-powered insights tailored to different forms of contracts. Unlike generic AI models, our 40+ AI solutions are built on high-quality project data and can be customised for specific business needs.
- Enhanced Insights: Our AI delivers twice the accuracy of traditional models, analysing millions of project issues and team interactions to provide more relevant recommendations.
- Context-Aware Tracking: Instead of relying on static keyword searches, our AI understands project issues in full context, helping teams make informed decisions.
- Smart Trackers: Customisable tools that uncover key trends, track risks, and measure project success from day one.
- Automated Forecasting: With BI Forecast, AI-driven contract warnings and predictive cost insights help teams eliminate guesswork and resolve risks faster.
- Seamless Integration: Our BI Coach and Integration Hub enhance productivity by integrating AI-driven insights directly into existing project workflows.
This is just the beginning. Watch this space as we roll out even more AI-powered tools designed to revolutionise contract management and project delivery.
Join the Conversation on AI in Construction
The construction industry is at a turning point. While it has been slow to embrace AI, the potential benefits are too significant to ignore. If you’re interested in learning more about how your organisation can reach its automation potential, you can download the Built Intelligence Contract Automation Whitepaper here for a quick assessment of your current adoption, and advice on your next steps.
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