This excerpt is from an article by David Boyland, Managing director, Asia and Maria Mingallon, Knowledge and information manager and digital AI lead, Asia Pacific, New Zealand and Australia
Optimising capital expenditure
Reducing capital expenditure (CapEx) is vital for ASEAN infrastructure projects. A McKinsey & Company report indicates that using digital technologies can cut project costs by up to 45%. This significant reduction is achieved through improved project planning, better resource allocation, and enhanced collaboration among stakeholders. One of the key areas where technology plays a vital role is in optimising design processes. A notable example of this is our use of AI to automate geotechnical data processing for design purposes. At a major ASEAN airport hub, we developed in-house solutions and partnered with a tech provider to automate data processing. This AI-driven solution not only reduced about 25% of the design costs but also enhanced the efficiency of the design process by digitising borehole logs, performing soil classification, and integrating geospatial data analysis. This approach enabled optimisation of the design process, ensuring better resource allocation and improved project outcomes.
Accelerating project timelines
Speeding up project timelines is essential for reducing overall costs and improving delivery efficiency. The Master Plan on ASEAN Connectivity 2025 (MPAC 2025) highlights the importance of coordinating resources across the full lifecycle of infrastructure projects. Integrating digital technologies, such as AI-driven project management tools, allows infrastructure projects to be completed more quickly and efficiently, reducing delays and cost overruns10. This approach ensures that projects are not only faster but also more resilient and sustainable.
Enhancing operational efficiency and asset management
A common issue with renewable energy is the inconsistency of variable renewable energy (VRE), which demands improvements in grid flexibility to accommodate more VRE inputs. Artificial intelligence can manage this inconsistency by providing advanced digitalisation, demand response management, and storage solutions. AI-driven technologies optimise grid flexibility for integrating more VRE inputs and enhance predictive analytics for better forecasting and maintenance, ensuring a reliable and efficient energy infrastructure. Mott MacDonald leverages AI and machine learning to more precisely forecast electricity demand enabling grids to operate with a greater degree of reliability confidence. Typically, AI improves forecasting accuracy by 25%, which feeds through to a reduction in ancillary services cost. Savings come principally from fuel efficiency and reduced need for reserve generating capacity, and reduced grid disruption and restoration costs. We have partnered with Above Surveying to use AI technology to deliver enhanced quality and efficiency of solar plant design, construction, and operation by providing accurate data and digital models. For asset management, AI-driven predictive analytics help forecast when maintenance is needed, which means less downtime and longer-lasting assets.