< PreviousA Southeast Asian Perspective The Impact of AI on the Construction Industry Artificial Intelligence (AI) is rapidly emerging as a transformative force across industries—and construction is no exception. Although traditionally seen as slow to embrace digital change, the construction sector in Southeast Asia is beginning to recognise the immense potential of AI technologies to drive greater efficiency, safety, and sustainability. From intelligent project scheduling and predictive maintenance to drone surveillance and generative design, AI is reshaping how projects are planned, executed, and maintained. In Malaysia, this digital shift is aligned with national efforts such as the Construction 4.0 Strategic Plan, the Construction Industry Transformation Programme (CITP), and the Construction Digitalisation Roadmap, championed by the Construction Industry Development Board (CIDB). While countries like Singapore are already making strong headway in AI-driven construction, the region as a whole still faces considerable challenges: digital skill gaps, high costs of adoption, limited data infrastructure, and uneven policy readiness. Here, Master Builders Journal explores the impact of AI on the construction industry from a Southeast Asian perspective, with a focus on Malaysia. Key use cases are highlighted, as well as regional adoption trends, strategic alignment with policy goals, and the challenges that must be addressed to realise the full potential of AI. We also look at the critical role of workforce development, regulatory support, and cross-border collaboration in building a future-ready, tech-driven construction ecosystem. AI and the Fourth Industrial Revolution in Construction Artificial Intelligence (AI) has evolved from a buzzword into a powerful SPECIAL FEATURE 28 MASTER BUILDERS JOURNAL #135to input specific constraints—budget, space, materials—and receive multiple design options optimised by algorithms. These tools are particularly useful in dense urban environments such as Kuala Lumpur or Jakarta, where space optimisation is critical. In Malaysia, the integration of AI into Building Information Modelling (BIM) is gaining traction. AI-enhanced BIM can automatically detect clashes, optimise spatial layouts, and simulate construction sequences before ground is broken. These capabilities significantly reduce design errors and minimise costly rework during construction. AI in Project Scheduling and Resource Management One of the most practical uses of AI in construction is predictive project scheduling. AI algorithms can analyse historical project data to forecast potential delays, suggest optimal task sequences, and identify resource bottlenecks. This technology is particularly beneficial for large-scale infrastructure projects such as railways, highways, or high-rise developments, where complexity and multiple dependencies often lead to delays. Singapore-based firms are already using AI platforms to manage labour, equipment, and materials more efficiently. In Malaysia, early adopters among Grade 7 (G7) contractors are beginning to explore AI for resource planning, helping them stay on track amid rising costs and labour shortages. AI in Construction Site Monitoring and Automation AI-powered drones, robotics, and IoT (Internet of Things) sensors are transforming on-site construction activities. Drones equipped with computer vision can map and inspect sites in real time, feeding data into AI systems that track progress against project milestones. Some AI tools can even detect unsafe behaviours—such as workers not wearing helmets—and trigger alerts to supervisors. In Thailand and Vietnam, construction companies are piloting AI-driven camera systems that monitor productivity and compliance with safety protocols. Malaysia is also seeing the emergence of AI-powered mobile inspection apps, where photos taken on-site are analysed instantly to identify structural anomalies or defects. AI in Safety and Risk Management Worksite accidents remain a serious concern in Southeast Asia. AI is proving to be a game-changer in enhancing safety through predictive analytics. By analysing incident reports, weather data, workforce rosters, and equipment logs, AI can flag high-risk periods or zones on a job site before accidents happen. In Indonesia, a local construction- tech startup has developed a safety management platform that uses AI to predict fall risks and equipment malfunctions. Such tools could greatly benefit Malaysian contractors seeking to improve safety ratings under CIDB’s Safety and Health Assessment System in Construction (SHASSIC). AI in Quality Control and Cost Management AI is helping project managers maintain quality while keeping costs in check. For example, machine learning models can detect early signs of structural stress or design inconsistencies from sensor data or site images. These systems reduce the reliance on manual inspections and accelerate the quality assurance process. Cost estimation is another area where AI excels. Algorithms trained on historical project costs and market trends can generate more accurate forecasts than traditional methods. This is especially helpful in public sector projects, where transparency and budget discipline are critical. AI in Maintenance and Facilities Management Post-construction, AI continues to deliver value in the operations and maintenance phase. Smart buildings are increasingly equipped with sensors that monitor energy usage, air quality, and mechanical systems. AI analyses this data to predict maintenance needs, thereby extending asset life and reducing unplanned downtime. Singapore’s Housing Development Board (HDB) has deployed AI to monitor lift performance across its estates, using predictive maintenance to reduce service disruptions. In Malaysia, property developers are exploring similar solutions in large mixed-use developments and commercial buildings. AI’s diverse applications in construction demonstrate its potential not just as a tool for automation, but as a strategic enabler of value creation. Across Southeast Asia, from design studios in enabler of innovation, efficiency, and competitiveness across a range of sectors. In the context of construction, AI refers to the use of intelligent algorithms and systems—often incorporating machine learning, computer vision, robotics, and big data analytics—to support smarter planning, execution, monitoring, and maintenance of infrastructure projects. Globally, the construction industry has long struggled with issues such as cost overruns, labour inefficiencies, safety hazards, and slow project delivery. These longstanding challenges have made the sector a prime candidate for technological disruption. The Fourth Industrial Revolution, marked by the convergence of physical and digital technologies, is ushering in a new era for construction, where data-driven decision-making and automation are key to staying competitive. In Southeast Asia, rapid urbanisation, population growth, and large-scale infrastructure investments are putting pressure on construction stakeholders to build faster, smarter, and more sustainably. Countries like Singapore, Indonesia, and Malaysia are at various stages of digital transformation in construction, with AI playing an increasingly prominent role. In Malaysia, CIDB has recognised the need to future-proof the industry by integrating digital technologies into its strategic frameworks, including the Construction 4.0 Strategic Plan and CITP. Use Cases of AI in Construction: Global Trends with Southeast Asian Examples The application of AI in construction is no longer theoretical—it is already transforming how buildings and infrastructure are designed, built, and managed. Around the world, construction firms are increasingly leveraging AI to solve complex problems, reduce inefficiencies, and improve decision-making across the project lifecycle. In Southeast Asia, although adoption is still in its early stages compared to North America or Europe, the momentum is building. Governments, developers, and technology providers are beginning to experiment with—and in some cases, institutionalise—AI-driven construction practices. AI in Design and Planning: Enhancing Precision and Creativity AI is revolutionising the way architects and engineers approach design. Tools such as generative design allow users COVER FEATURE SPECIAL FEATURE 29 MASTER BUILDERS JOURNAL #135Singapore to job sites in Kuala Lumpur, the shift towards AI is already underway— albeit unevenly. The State of AI Adoption in Southeast Asia’s Construction Industry The construction sector across Southeast Asia stands at the crossroads of tradition and transformation. While the region has long grappled with productivity stagnation, labour shortages, and inconsistent safety standards, the arrival of AI technologies offers a chance to redefine its trajectory. However, the current state of AI adoption is uneven, shaped by differing levels of digital maturity, government support, infrastructure development, and industry readiness across ASEAN nations. Among Southeast Asian countries, Singapore leads the way with one of the most digitised construction sectors in the region. Through initiatives such as the Integrated Digital Delivery (IDD) framework and government funding under the Building and Construction Authority (BCA), Singaporean contractors have embraced AI in areas such as project coordination, site monitoring, and facilities management. Digital twins, predictive analytics, and AI-enhanced BIM have become increasingly common in large-scale public and private developments. Malaysia, in contrast, is at an earlier phase of AI adoption, but notable progress is being made. CIDB Malaysia has launched a number of digitalisation initiatives, including the Construction 4.0 Strategic Plan, and the CITP 2016–2020, which call for the use of smart technologies to enhance productivity, sustainability, and quality. Under these frameworks, AI is identified as one of the enabling technologies to be integrated into the construction ecosystem, particularly in conjunction with BIM and the Industrialised Building System (IBS). However, widespread adoption of AI tools remains limited to larger contractors and developers with the resources and capacity to invest in innovation. Many small and medium- sized construction firms (SMEs)—which make up the bulk of the industry—still face major hurdles, including high upfront costs, limited awareness of AI’s potential, and a lack of in-house digital expertise. Furthermore, the absence of widely accepted standards for construction data makes it difficult to fully harness the capabilities of AI, which relies heavily on high-quality, structured information. Other countries in the region, such as Thailand, Vietnam, and Indonesia, are also beginning to explore AI integration, particularly in mega-projects and smart city developments. Yet, in most cases, AI adoption is still experimental rather than systemic. Government involvement and public-private partnerships will be crucial to scale up these efforts beyond a few flagship projects. As Southeast Asia accelerates its post-pandemic infrastructure push, AI adoption will likely be shaped by how well each country can align its construction sector with national digital economy agendas. In Malaysia, continued support from CIDB, alongside industry leadership and educational reform, will be essential to move from isolated pilot projects to sector-wide transformation. AI and Malaysia’s Construction Transformation Goals Malaysia’s commitment to modernising its construction sector is well established. Through policy instruments such as the Construction 4.0 Strategic Plan and the CITP, CIDB Malaysia has set ambitious goals: to raise productivity, improve safety and quality, and promote environmental sustainability. In this context, AI is recognised not merely as a technological innovation but as a strategic enabler of transformation. AI aligns closely with several of the CITP’s four thrusts—Quality, Safety and Professionalism; Environmental Sustainability; Productivity; and Internationalisation. For instance, AI-powered safety monitoring systems and predictive analytics contribute directly to improved safety standards at construction sites. Similarly, generative design and energy modelling tools powered by AI support sustainable building practices, helping the industry reduce its environmental footprint. Notably, Malaysia’s National Artificial Intelligence Roadmap 2021–2025, led by the Ministry of Science, Technology and Innovation (MOSTI), identifies the construction sector as one of the industries with high potential for AI integration. This reinforces a whole-of- government approach to digitalisation and creates synergy between national digital economy goals and sector-specific reforms. Despite these policy commitments, a gap remains between ambition and implementation. The majority of local contractors—particularly SMEs—continue to struggle with the foundational steps of digital adoption, such as using BIM or digital project management tools. For AI to become more mainstream, capacity- building programmes, affordable access to digital platforms, and incentives for early adopters must be scaled up. CIDB’s ongoing initiatives in training, certification, and awareness-building are vital to ensuring that AI adoption aligns with the broader national goal of a resilient, competitive, and future-ready construction industry. Challenges and Risks of AI Adoption in the Regional Context While the promise of AI in construction is compelling, its adoption across Southeast Asia is not without challenges. The region’s construction industry is highly fragmented, labour-intensive, and historically slow in embracing digital innovation. Several structural, operational, and socio-economic hurdles must be addressed before AI can be integrated at scale. A fundamental issue is the lack of structured data. AI depends on large volumes of high-quality, well-labelled data to function effectively. In many Southeast Asian construction projects, data is still collected manually or inconsistently, making it difficult to feed AI models with reliable information. Furthermore, interoperability between software platforms is limited, especially among SMEs that rely on legacy systems or spreadsheets for project tracking. Cost remains a significant barrier. AI tools and platforms—especially those involving computer vision, robotics, or predictive modelling—require substantial upfront investment. This creates a divide between large firms with capital to experiment and smaller players who must prioritise short-term cost management over long-term innovation. Additionally, many firms lack clarity on the return on investment (ROI) of AI, which can delay decision-making and adoption. Human capital is another pressing issue. There is a shortage of skilled professionals who understand both construction workflows and data science. Without a digitally literate workforce, even the best AI tools will be underutilised. Upskilling efforts in the region are still fragmented, with few academic or vocational institutions offering programmes that bridge SPECIAL FEATURE 30 MASTER BUILDERS JOURNAL #135construction and AI-related disciplines. From a regulatory standpoint, standards and policies governing AI in construction are still evolving. Issues such as data privacy, liability in AI-driven decision-making, and the ethical use of surveillance technologies have yet to be comprehensively addressed in most ASEAN countries. This regulatory uncertainty can create hesitancy among firms, especially in public sector projects where compliance is critical. Finally, there are cultural and organisational barriers. Construction remains a risk-averse industry where traditional practices dominate. Resistance to change, coupled with a lack of success stories from within the region, means that many decision-makers are still sceptical of AI’s relevance to their day-to- day operations. Overcoming these challenges requires a coordinated effort across governments, industry bodies, educational institutions, and tech providers. In Malaysia, this means scaling up CIDB’s digitalisation support for SMEs, strengthening industry-academia linkages, and creating incentives for AI experimentation— especially in areas aligned with national infrastructure priorities. Building Capacity and Innovation Ecosystems for AI in Construction For Southeast Asia—and Malaysia in particular—to fully harness the transformative potential of AI in construction, a robust ecosystem that supports capacity building, innovation, and collaboration is essential. At the heart of this ecosystem are people, processes, and partnerships. Human capital development is the foundation. AI tools are only as powerful as the people who design, operate, and maintain them. There is a growing need for a new generation of professionals fluent in both construction management and digital technologies. Vocational institutes, universities, and training centres must update curricula to include modules on data analytics, AI applications, and digital construction workflows. CIDB Malaysia, through its academy and MyConstruct initiative, has already begun this journey—but broader collaboration with the private sector and academia is needed to build a steady pipeline of skilled talent. Public-private partnerships play a critical role in accelerating AI adoption. Tech providers, construction companies, and regulators must co-create solutions tailored to local contexts. Sandboxes for pilot projects, industry innovation grants, and joint research centres can serve as low-risk environments for experimentation. Malaysia’s National Technology and Innovation Sandbox (NTIS) and collaborations led by the Malaysia Digital Economy Corporation (MDEC) offer promising models to build upon. A successful AI-driven construction ecosystem also requires interoperable digital infrastructure. Construction firms need access to shared platforms for data exchange, performance benchmarking, and compliance tracking. Clear data standards—co-developed by CIDB and industry stakeholders—will improve trust, transparency, and the efficacy of AI tools across projects and firms. Lastly, innovation ecosystems flourish where vision meets incentive. Government procurement policies can drive digital transformation by prioritising AI-ready contractors. Equally, industry leaders must be willing to invest beyond compliance, using AI not only to solve problems but to create value—whether through enhanced design, faster delivery, or reduced environmental impact. Outlook: What’s Next for AI in the Construction Industry? As Southeast Asia’s economies recover and rebuild following the pandemic, infrastructure and housing development will continue to be national priorities. AI is poised to play an increasingly strategic role—not just as a technical solution, but as a catalyst for reimagining how the built environment is conceived, constructed, and maintained. In the next five to ten years, we can expect to see wider adoption of AI in high-stakes areas like climate- resilient design, carbon tracking, and automated project management. Integration with emerging technologies such as 5G, IoT, and digital twins will further enhance AI’s ability to deliver real-time, actionable insights across the construction value chain. For Malaysia, the challenge is clear: to scale AI adoption from isolated use cases to systemic transformation. This requires vision, leadership, and sustained collaboration across sectors. As CIDB continues to champion digitalisation, the country has an opportunity to position itself as a regional leader in smart and sustainable construction. Conclusion AI is no longer a distant concept—it is already shaping the future of construction in tangible ways. From design and planning to safety, quality control, and facilities management, AI offers powerful tools to enhance efficiency, reduce risk, and improve outcomes. In the Southeast Asian context, adoption is accelerating, but still faces structural, financial, and cultural barriers. Malaysia, through its national roadmaps and CIDB-led initiatives, is laying the groundwork for a digital-first construction industry. However, real transformation will depend on how quickly the industry can build capacity, create data infrastructure, and nurture an innovation-friendly ecosystem. The journey ahead will not be without challenges, but the opportunities far outweigh the risks. For those willing to embrace change, AI represents more than a tool—it is a pathway to a smarter, safer, and more resilient construction future. COVER FEATURE SPECIAL FEATURE “AI is reshaping how construction projects are planned and executed.” 31 MASTER BUILDERS JOURNAL #135P O W E R D I S T R I B U T I SPECIAL FEATURE To better understand how AI is influencing the local construction landscape and what lies ahead, Master Builders Journal spoke to Mohammad Faizal Abdul Hamid, General Manager, Technology Development Division, CIDB Malaysia, for his insights on current developments, challenges and the future vision of AI in construction. How does CIDB Malaysia view the role of artificial intelligence (AI) in shaping the future of the local construction industry? CIDB Malaysia views artificial intelligence (AI) as a powerful enabler in driving the transformation of the construction industry towards a more productive, efficient and sustainable future. AI is not merely a technological trend—it is a catalyst capable of addressing long- standing industry challenges such as low productivity, safety concerns, cost overruns and labour dependency. We believe AI can enhance decision- making across the project lifecycle—from planning and design to construction and asset management—by providing real-time insights, predictive analytics and automation capabilities. As Malaysia advances its digital economy agenda, AI will play an increasingly important role in elevating the construction sector into a knowledge- and technology-based industry. What are the most promising applications of AI currently being used or piloted in Malaysia’s construction sector? Several AI applications are beginning to gain traction within Malaysia’s construction landscape, particularly in the areas of: — Predictive maintenance and asset management – AI-powered systems are being used to monitor infrastructure health and forecast maintenance needs before failures occur, especially in large infrastructure projects. — Safety monitoring and risk mitigation – Using computer vision and real-time analytics, AI helps detect safety hazards, monitor worker behaviour and enforce compliance with safety protocols on site. — Project scheduling and resource optimisation – AI tools assist project managers in forecasting delays, allocating resources more effectively and identifying inefficiencies in workflows. — Design optimisation and generative design – AI algorithms generate multiple design options based on specific parameters, helping architects and engineers arrive at cost-effective, sustainable solutions. These pilot programmes are typically led by major contractors and infrastructure players, with growing interest from local tech firms and universities to localise these innovations for Malaysian use cases. How does the adoption of AI align with CIDB’s Construction 4.0 Strategic Plan objectives, particularly in terms of productivity and digitalisation? AI adoption is closely aligned with the core pillars of CIDB’s Construction 4.0 Strategic Plan—namely Digitalisation, Q&A with Mohammad Faizal Abdul Hamid General Manager, Technology Development Division, CIDB Malaysia 34 MASTER BUILDERS JOURNAL #135COVER FEATURE SPECIAL FEATURE proactive intervention before accidents occur. AI can also automate inspections by analysing data from drones, wearables and IoT sensors to detect structural weaknesses, environmental risks or non-compliance with CIDB’s Construction Industry Standard (CIS) documents. Additionally, AI-driven reporting tools enable contractors to maintain more accurate and timely safety records, enhancing transparency and regulatory compliance. How is CIDB preparing the construction workforce to work alongside AI tools, particularly in terms of training and upskilling? Workforce readiness is a cornerstone of CIDB’s digital transformation agenda. We recognise that effective AI adoption requires a shift in skills, mindset and workplace culture. CIDB has launched various initiatives to prepare the workforce for the digital future. These programmes are designed not only to enhance skills but also to address concerns about automation by demonstrating how AI can augment, rather than replace, human capabilities. What collaborations is CIDB pursuing with local academia, startups or global partners to foster AI innovation in construction? Collaboration is essential to driving innovation in construction-focused AI. CIDB actively fosters partnerships across three key fronts: academia, technology companies and international organisations. These collaborations are vital to ensuring that Malaysia’s construction sector does not merely adopt AI passively, but actively contributes to global innovation in construction technology. How can AI help Malaysia’s construction industry meet sustainability goals, such as reducing carbon emissions or improving resource efficiency? AI can accelerate sustainable construction in several impactful ways: — Energy and resource optimisation – AI analyses data from smart sensors to reduce energy usage on sites, optimise material consumption and minimise waste, contributing directly to carbon reduction and cost savings. — Sustainable design – Generative design tools powered by AI propose the most efficient building layouts based on environmental and structural parameters, helping professionals make greener decisions. — Carbon tracking and reporting – AI enables more accurate monitoring of supply chain carbon emissions, supporting sustainability reporting in line with frameworks such as the Green Technology Master Plan (GTMP), Low Carbon Cities Framework (LCCF), and guidelines by MGTC under the Ministry of Environment and Water (KASA/NRECC). — Lifecycle analysis – AI can simulate and assess a building’s environmental impact throughout its lifecycle, facilitating green certification under schemes like GreenRE or MyCREST. Sustainability is a central focus of CIDB’s Construction 4.0 agenda, with AI a key enabler in aligning construction practices with national and global climate goals. Looking ahead, what is CIDB’s long- term vision for AI in construction, and how will it help future-proof the industry? CIDB envisions AI as a foundational element of a resilient, high-performing and sustainable construction industry in Malaysia. Our long-term goal is to create an ecosystem where AI is seamlessly integrated throughout the construction value chain—from planning and design through to operations and maintenance. Over the next decade, we foresee: — Fully digitalised construction sites with AI-driven monitoring and autonomous equipment — Data-centric project delivery powered by AI to improve accuracy, efficiency and risk management — A new generation of digitally proficient construction professionals who co- create value with AI — Smarter regulatory systems enhanced by AI for monitoring, licensing and certification To realise this vision, CIDB will continue investing in policy development, workforce transformation and strategic partnerships—ensuring Malaysia’s construction sector is not only AI-ready, but positioned as a leader in innovation and sustainability. Industrialisation and Professionalisation. AI plays a key role in accelerating digital transformation, a major enabler for enhancing productivity and competitiveness in the sector. Under the Construction 4.0 roadmap, CIDB promotes integration of tools such as AI, BIM, IoT, robotics and big data analytics into construction practices. AI, in particular, supports our goals to: — Improve productivity through automation and predictive planning — Enhance decision-making with data- driven insights — Support quality assurance and risk mitigation — Facilitate lifelong learning and workforce upskilling in tandem with technology adoption We also collaborate with strategic partners to promote AI awareness, capacity-building and practical implementation across the ecosystem. What are the key barriers to AI adoption among Malaysian contractors, especially small and medium-sized players, and how is CIDB addressing them? While interest in AI is strong, several barriers hinder its broader adoption, particularly among SMEs. These include: — High upfront costs for AI tools and digital infrastructure — Shortage of technical expertise and digital talent — Limited understanding of AI’s practical benefits and ROI — Fragmented digital adoption across project value chains, making integration challenging To overcome these hurdles, CIDB has launched initiatives aimed at helping industry players, particularly SMEs, build foundational knowledge in digital technologies, including AI. What role can AI play in enhancing construction site safety and compliance with CIDB regulations? AI can be a game-changer in improving safety and compliance on construction sites. One promising application is the use of computer vision and AI-powered surveillance systems to monitor worker behaviour and detect unsafe practices or hazards in real time. 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