On October 23, 2026, Dr. Cao Longjun, co-founder of the Hong Kong Artificial Intelligence Technology Development Research Institute (HK-AITRI), Director Wu Lei of GreenTech Carbon Environment Technology, and Mr. Stanley, who graduated from The Hong Kong Polytechnic University (PolyU), conducted in-depth discussions on urban renewal, low-carbon transformation in the construction industry, zero carbon park construction, and entry points for AI technology implementation, exploring innovative paths for AI to help the construction industry achieve low-carbon "measurable and verifiable".
It is reported that Stanley has long-term practical experience in urban construction and renewal projects, and is deeply committed to the direction of low-carbon and sustainable development in architecture. During the exchange, he proposed that although the construction industry is currently facing temporary development pressure, the long-term evolution path is clear: the large-scale application of low-carbon building materials and the systematic construction of zero carbon parks are the core mainlines for the industry to achieve the dual carbon goal. This judgment echoes the academic research conclusion: according to the calculation of the Building Energy Efficiency Research Center of Tsinghua University, in 2020, the operating energy consumption of domestic buildings accounted for 21% of the total energy consumption of the whole society, and the supporting carbon emissions accounted for 19% of the national total. The building operation process belongs to the key sector of carbon emissions; The total carbon emissions of over 2000 national and provincial industrial parks in China account for 31% of the country's total. The energy-saving and carbon reduction transformation of massive existing buildings and industrial parks is the most determined research and industrialization direction for the low-carbon construction track.
Based on the top-level framework of dual carbon, both sides analyze the policy evolution logic from both academic and industrial perspectives: the dynamic expansion of the national low-carbon energy-saving material catalog and the continuous promotion of zero carbon park pilot implementation are essentially to continuously improve the recognition paradigm of low-carbon attributes and establish standardized benchmarks for carbon accounting in the construction industry. In the seminar, Hilton Hotels Group's ESG practices were used as a reference case to confirm that low-carbon transformation is not simply a compliance cost. Sustainable governance capabilities can be accumulated into a company's brand value and asset premium, providing a reference sample for academic research and commercial implementation in the construction industry.
Looking at the global climate governance landscape, the external constraints brought by the EU CBAM carbon border adjustment mechanism have made the credibility of carbon data a new research topic. The export of high carbon categories such as steel, aluminum, and chemical building materials in China will face the impact of carbon costs, and the potential risk of carbon tariff rules spreading outward will force the establishment of a domestically recognized and internationally recognized carbon accounting system. Low carbon is no longer a voluntary bonus for enterprises, but a requirement for cross-border trade access. The foundation of this system is the measurability and verifiability of carbon emission data.
Based on this academic exchange, all parties have reached a consensus that artificial intelligence, especially explainable artificial intelligence (XAI), is a key technological carrier supporting the trustworthiness of building carbon data. The emission sources of building scenes are scattered, and direct emissions and indirect emissions caused by electricity and heat are intertwined. The accuracy of traditional static accounting methods is insufficient. An AI framework that integrates IoT perception and energy consumption mechanism models can achieve temporal and fine-grained dynamic measurement of carbon data; The traceable reasoning ability possessed by XAI can fully retain accounting logic, support third-party audit verification, match domestic low-carbon directory supervision, CBAM declaration, and ESG information disclosure requirements, and transform qualitative low-carbon concepts into verifiable and credible quantitative evidence. This implementation model is also in line with the progressive research chain of RAI responsible AI, ESG sustainable management, SDGs, and the United Nations Sustainable Development Goals: putting ESG standards in the forefront of AI algorithm development, using responsible AI to control model risks, output credible carbon data, and ultimately serve the global sustainable development agenda.
Dr. Cao Longjun is currently pursuing a PhD in Artificial Intelligence at the School of Data Science, Lingnan University, and holds a PhD in Sustainable Development from the School of Management, Politecnico di Milano (PoliMi). Lingnan University has long been committed to promoting the United Nations Sustainable Development Goals (SDGs) through innovative technology, deeply integrating the concept of sustainable development into teaching and research systems, fully demonstrating the interdisciplinary research advantages of the university in the fields of data science and sustainable development, and providing solid academic support for the interdisciplinary research on AI empowering green buildings. The exchange believes that the zero carbon transformation of the construction industry is a typical interdisciplinary topic, involving multiple fields such as civil engineering, energy engineering, computational mathematics, artificial intelligence, environmental economics, etc. It is a long-term systematic project that cannot be separated from policy standards, low-carbon new materials, intelligent algorithms, and industrial capital. In the future, HK-AITRI will rely on cross university academic networks to gather research forces in low-carbon buildings, intelligent construction, and explainable AI directions. Together with industry partners, we will continue to carry out empirical research and pilot implementation of the "AI+Zero Carbon Park", deepen industry collaboration, empower green buildings with AI technology, build a carbon measurement technology base that is both scientific and practical for the construction industry, contribute solutions to global carbon reduction goals, and provide measurable, verifiable, and trustworthy academic solutions and industrial paths for low-carbon governance in the construction field.
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HONG KONG ARTIFICIAL INTELLIGENCE RESEARCH INSTITUTE (HK-AITRI) is affiliated with Hong Kong AI Technology Development Limited and was established by a group of scholars and industry practitioners dedicated to transforming industries with AI technology. The research institute is rooted in Hong Kong, building an AI industry laboratory and a collaborative platform between the institute and enterprises, aiming to fill the gaps in the manufacturing innovation system, create a multi-party collaborative innovation carrier, link various enterprises, universities, and government agencies, and jointly promote the high-quality development of advanced manufacturing industries. The research institute focuses on the practical application of physical AI and intelligent agents, and adopts a project-based approach to output research teams and cutting-edge AI technology capabilities, breaking down barriers between technology research and development and industry demand, helping physical enterprises achieve low-cost intelligent upgrades, and creating an industrial AI industry university research collaborative innovation platform for the Greater Bay Area.
