The construction industry is experiencing a growing interest in incorporating artificial intelligence (AI) technologies to streamline processes and mitigate project liability risks. While the industry has been slow to adopt digitalized data processing models, the potential value of AI-driven solutions cannot be ignored.
Analytics solutions powered by AI have the capability to identify and analyze project-related delays, which are often the cause of supply chain disputes. By continuously monitoring historic project datasets, these solutions can refine the accuracy of predicted risks as the project progresses and more data becomes available. However, the effectiveness of these predictions relies heavily on the quality and breadth of data provided by the supply chain and project administrators.
To encourage greater “buy-in” from the supply chain and improve the reliability of the dataset, contractually mandating the contribution of accurate project data at the outset of a project could be beneficial. By specifying consequences for non-compliance, construction organizations can incentivize the adoption of AI-driven analytics solutions and enhance the reliability of risk predictions.
In addition to analytics solutions, large language models (LLMs) powered by AI can assist in various cost and time-consuming activities, such as summarizing contract documents and generating payment-related notices. However, like analytics solutions, the accuracy and usefulness of LLMs depend on the input and review of data by individuals.
For a more comprehensive and technologically collaborative approach, AI-powered smart contracts combined with building information modeling (BIM) can offer enhanced monitoring of contract terms, areas of non-compliance, and changes to contract terms. BIM provides an accurate digital record of the design and construction process, while smart contracts automate contract generation and can adapt to evolving project data.
Although AI-driven technologies can lead to earlier identification and allocation of responsibility for project-related risks, they are unlikely to replace independent administrators of contract terms in the construction sector. Instead, AI can complement their role and improve the management of projects when conflicts arise within the supply chain.
As the construction industry faces more stringent building safety laws, there is an increasing openness to adopting improved methods to manage project delivery and mitigate liability risks. However, significant investment in the development of AI-based technologies is necessary before they can reliably inform parties of potential project liability risks.
Can AI completely replace human administrators of contract terms in the construction industry?
No, AI is unlikely to replace independent administrators of contract terms in the construction sector. However, AI can complement their role by enhancing the management of projects and improving efficiency.
How can contractually mandating accurate project data contribute to the effectiveness of AI-driven analytics solutions?
By mandating the contribution of accurate project data from the supply chain, construction organizations can improve the reliability of the dataset used by AI-driven analytics solutions. This can enhance the accuracy of risk predictions and encourage greater adoption of AI technologies.
What are the limitations of AI-driven solutions in the construction industry?
AI-driven solutions, such as analytics products and large language models, depend on the quality and input of data by individuals. Their accuracy and usefulness are limited by human biases and errors. Furthermore, their effectiveness relies on the willingness of the supply chain to actively participate in data sharing.
- Construction Manager – https://www.constructionmanagermagazine.com/