Leveraging AI for Sustainable Material Sourcing. By Amr Nader, Co-Founder & CEO at A³&Co, and Jaap Bastiaansen at Nexus Climate
The building and construction industry is one of the largest contributors to global greenhouse gas emissions, responsible for nearly 40% of total energy-related carbon emissions. This is driven by energy use in buildings, material production like concrete and steel, and energy-intensive construction activities. According to the United Nations Environment Programme (UNEP), the building sector consumes about 30% of the world’s total energy output, underscoring its massive environmental impact.
In the Middle East and North Africa (MENA) region, this problem is particularly pressing due to rapid urbanization and infrastructure expansion. The International Energy Agency (IEA) predicts that building sector emissions in MENA could rise by 25% by 2030 if significant sustainability efforts are not implemented. The region’s reliance on traditional, carbon-heavy materials adds to the complexity of tackling emissions in construction.
Transitioning to sustainable building practices, particularly in material sourcing and supply chain management, a transformative role, requires addressing the challenges of limited local production and fragmented global supply chains. Significant investment in alternative materials R&D and scaling regional production capacities is essential to reduce reliance on imports and transport emissions.
“Decarbonization and digital maturity are not standalone goals but mutually reinforcing priorities that, when pursued together, can transform the built-environment sector into a low-carbon, resilient industry.” Amr Nader
The global supply chain for construction is highly fragmented and lacks transparency, making it difficult to consistently verify and source green materials. Costs fluctuate, suppliers are inconsistent, and environmental standards vary by region. In the MENA region, these challenges are further compounded by limited local production of green materials and the high costs of imports.
Additionally, manual procurement processes are outdated and inefficient, unable to handle the complexity of modern projects. As a result, sustainability often takes a backseat to cost, convenience, and speed.
The Solution: AI-Driven Material Sourcing and Supply Chain Optimization
AI provides a powerful solution to the complexities of material sourcing and supply chain management. Through its ability to process vast datasets in real time, AI enables the construction industry to optimize procurement, predict material availability, and evaluate the sustainability credentials of different suppliers and materials.
AI’s predictive analytics can forecast supply chain disruptions, helping companies anticipate and mitigate risks like supplier shortages or geopolitical risks. By using machine learning to recommend materials with the lowest carbon footprint, AI helps decision-makers balance sustainability with cost-effectiveness.
In regions like MENA, where material imports drive up costs and emissions, AI can support building localized supply chains for green materials, reducing transport-related carbon footprints and increasing resilience against global disruptions. Governments and industry players must work together to create open-access platforms to democratize AI’s benefits and align with global sustainability standards like LEED and BREEAM. Pilot projects demonstrating AI’s efficacy in material sourcing and emissions reduction are vital to overcome adoption scepticism.
Data-Sharing Challenges and the Need for Collaboration
The effectiveness of AI in optimizing material sourcing and supply chain management depends heavily on access to comprehensive data from across the supply chain. However, sharing data between suppliers, manufacturers, and logistics providers is challenging due to data privacy concerns, competition, and inconsistent data formats. The fragmented nature of the construction industry further complicates the flow of data, creating bottlenecks that hinder AI’s ability to deliver accurate insights.
To fully harness the potential of AI in creating more sustainable supply chains, there is an urgent need for increased transparency and collaboration across the industry. Establishing open data platforms or public-private partnerships that promote data sharing could significantly enhance the ability of AI systems to solve complex sourcing challenges. By creating a shared ecosystem of data, stakeholders can generate actionable insights that accelerate the transition to greener building practices.
Focus on building localized supply chains for low-carbon materials in the MENA region, including partnerships with green startups and academic institutions.
Collaboration Across Ecosystem Players: The Path Forward
The successful adoption of AI in the built environment requires a collaborative effort among startups, corporates, academia, and governments. Startups are driving innovation by developing AI-driven solutions, but often require partnerships with corporates to scale these technologies. Corporates, particularly large construction firms, possess the resources to implement AI on a broad scale, significantly enhancing efficiency, cost savings, and sustainability.
Academia plays a vital role in advancing research and providing the technical expertise needed to refine AI algorithms and evaluate their real-world impact. Governments create the necessary regulatory frameworks and incentives to promote the adoption of sustainable materials and AI-driven processes. In regions like MENA, where public sector involvement is crucial for large infrastructure projects, government policies can foster collaboration between private sector players and ensure that sustainability goals are met.
Broadening the focus to include complementary initiatives, such as promoting circular economy practices, scaling low-carbon technologies, and integrating renewable energy into operations, can amplify the impact of AI-driven solutions. Together, these ecosystem players can overcome the challenges of sourcing green materials and optimizing supply chains, using AI to create a more sustainable and efficient built environment.
As the world strives to decarbonize, the construction industry faces a significant challenge in transitioning to sustainable practices. AI offers a transformative solution by enabling better material sourcing, streamlined procurement, and enhanced supply chain transparency. However, unlocking AI’s full potential requires collaboration across the ecosystem—startups, corporates, academia, and governments must work together to build a more sustainable future. By doing so, the industry can reduce its carbon footprint while meeting the growing demand for infrastructure and urban development.
Considering these opportunities and challenges, establishing a MENA Chapter of the Industrial Decarbonization AI Coalition (IDIAC) is a logical step. This organization will facilitate and scale the use of AI in industry to accelerate decarbonization efforts. By focusing on education, awareness, and identifying sectoral opportunities, IDIAC aims to unlock the potential of AI and machine learning in supporting industrial decarbonization. Our mission is to enable advanced R&D, industry collaboration, and solutions development, particularly in the areas of AI for industrial processing and materials discovery. The MENA Chapter can champion advanced R&D, foster industry collaboration, and develop impactful solutions in AI for industrial processing, lifecycle emissions tracking, and materials discovery. This aligns with the region’s urgent need for sustainable building practices and innovative material sourcing solutions.
