TeamworX Indonesia
15 Sep 2026
Throwback to five years ago, engineers would have to spend hours of working time writing and reviewing thousands of pages of project documents. They would manually scan building specifications, cross-reference contracts, and compile reports before moving on to more complex engineering work.
Today, some of those tasks can be completed within minutes with the help of artificial intelligence (AI).
“AI helps us work faster and be more productive,” says Pracayasa Ade Putra, BIM Coordinator at TeamworX Indonesia.
However, this raises a further question: how far can engineers utilize AI in construction projects?
Automating Repetitive Documentation
Construction projects generate extensive documentation, such as technical specifications, contracts, requests for information (RFIs), submittals, transmittals, and daily reports. Manually working on the tasks would consume a significant portion of engineers’ productive time, which is better spent on the strategic decisions.
This is where engineers can utilize AI to automate repetitive and time-consuming tasks, such as:
● Extracting requirements from technical specifications.
● Organizing and categorizing data.
● Summarizing technical documents.
● Generating structured reports and documentation.
Recent research has demonstrated that AI-powered systems can process 1,000–1,500-page specifications and turn relevant submittal requirements into structured outputs. By reducing the time spent searching, copying, and formatting information, AI allows engineers to focus more on engineering analysis and strategic decision.
Beyond documentation, AI is also utilized to support the design process. In architectural workflows, generative AI can create design visualizations or renderings based on basic sketches or models within minutes.
“Manually, the rendering process took at least two hours of editing,” says Pracayasa.
Enhancing Accuracy and Cost Efficiency
In construction projects, documentation errors carry real financial consequences. Inaccurate information and delayed decision-making can lead to costly rework, schedule delays, and even disputes.
One area where AI implementation can show measurable impact is its integration with Building Information Modeling (BIM) through digital twins. By analyzing real-time project data, AI-powered systems can help identify potential issues, deviations, and risks earlier.
A recent study found that AI-powered digital twins could detect approximately 91.3% construction issues early, with 96.5% and 93.8% accuracy in detecting schedule deviations and budget variances, respectively.
Yet, AI should be viewed as a decision-support tool rather than autonomous decision-makers. The accuracy of AI-generated insights still depends heavily on the quality, completeness, and reliability of the underlying project data.
Human Verification Remains Non-Negotiable
It is true that AI can improve the speed, accuracy, and efficiency of construction workflows, particularly in documentation and data processing. However, final decisions and verification should remain the responsibility of qualified professionals.
Construction projects involve complex technical requirements, site-specific conditions, safety considerations, and professional judgment that cannot always be fully understood by an AI system.
AI-generated outputs must therefore be reviewed and validated by engineers or other qualified professionals before being applied to the project.
“We cannot delegate AI to make design decisions because doing so could result in serious or even catastrophic consequences,” says Pracayasa.
Ultimately, AI should not be seen as a replacement for construction professionals. Instead, its greatest potential lies in augmenting human capabilities like handling repetitive tasks, accelerating access to information, and supporting more informed decision-making.
Want to explore how AI can support your next construction project? Consult with our engineers to find the right solution for your needs.
References:
- Kalasapudi, VS, et al. Frontiers in Built Environment. “The overlooked frontier of AI in construction: conversational, document-native automation for administrative workflows”.
- Gudibandi, Siva Praneeth Reddy. International Journal of Scientific Research in Computer Science Engineering and Information Technology. “AI in Construction Project Management: Enhancing Efficiency and Reducing Costs”.
