New Zealand’s construction industry is bracing for a significant transformation with the rise of Artificial Intelligence (AI). Facing challenges like a shortage of labor, escalating construction costs, and interruptions by weather-related incidents, construction firms in the region are turning to innovative technologies to streamline their operations.
According to a recent report by Autodesk and Deloitte, the State of Digital Adoption in the Construction Industry 2024, the construction sector in AsiaPacific is encountering similar hurdles and is exploring AI as a solution. Sumit Oberoi, Senior Manager at Autodesk, highlighted that New Zealand construction is mirroring the challenges seen in Australia and other parts of AsiaPacific.
With disruptions caused by supply chain issues, rising costs, and labor shortages, the industry is seeking digital transformation to enhance productivity and address these pressing issues. The report surveyed 933 construction companies in six markets, revealing that 30% of Australian firms are already experimenting with AI software to boost efficiencies and tackle key industry problems.
Australia’s construction sector sees AI as a tool to combat labor shortages, high material costs, and supply chain disruptions. The adoption of generative AI technologies like ChatGPT and Github Copilot is gaining momentum, allowing companies to leverage past projects to inform new proposals efficiently.
A significant 33% of Australian construction companies have plans to integrate AI into their operations, with experts predicting that AI adoption could become as common as data analytics in the industry. Businesses are urged to start by piloting projects, establishing a digital champion, setting success metrics, building a digital ecosystem, and assessing their readiness for AI implementation.
As New Zealand’s construction sector plays a vital role in the economy, contributing 6.7% of real GDP and employing a substantial workforce, embracing AI and digital tools is crucial for sustained growth and competitiveness. The industry must prioritize data standardization and create a common data environment to pave the way for successful AI implementation in the future.
