Special Topic: Dialogues with ESG Global Leaders.

The SINA Finance ESG Ratings Center provides 14 ESG services including information, reports, training, and consulting, helping listed companies spread ESG concepts and improve ESG sustainable development performance. Click to view the ESG Ratings Center Service Manual. SINA Finance, Li Tao, reporting from Beijing.

Currently, global sustainable development has entered a period of deep transformation. Topics such as dual-carbon construction, ESG governance, and supply chain greening are being comprehensively implemented. However, multiple challenges including geopolitical conflicts, economic fluctuations, climate risks, and compliance barriers have plunged the industry into a dilemma where popularizing concepts is easy but achieving deep implementation is difficult. The penetration of AI technology has provided new opportunities for sustainable quantitative management, yet it has also brought secondary problems such as energy consumption and data distortion. The differentiated development of sustainable practices between China and the United States has further highlighted the controversy over the path of global green transformation.

Against this backdrop, we spoke with Professor Guo Dong of Columbia University for an in-depth discussion on core issues including the key breakthrough in global sustainable transformation, the two-way value of AI technology, the industry's decade of change, differences between Chinese and American practices, and the pain points in implementing sustainable management.

Professor Guo Dong stepped beyond the traditional perspective of ideals and proposed making resilience enhancement the core lever for sustainable development. He clarified the irreplaceable value and governance shortcomings of AI in sustainable quantitative management, comparatively analyzed the differences in context, driving forces, and capabilities between Chinese and American sustainable development, and, drawing on the core content of his new book, pointed out that the ultimate transformation of sustainable development is moving from innovative concepts to daily management, providing hard-hitting practical ideas for the sustainable transformation of enterprises and cities. The following is a transcript of the dialogue:

SINA Finance: Currently, there are numerous global sustainable development topics, from dual carbon and biodiversity to ESG disclosure and supply chain greening, and all parties are investing substantial resources. In your view, what is the most core lever or breakthrough point for global sustainable development today? Which areas, if deepened and solidly implemented, could truly leverage overall sustainable transformation?

Guo Dong: If I were to choose one most core lever, I would say: enhancing resilience. Having resilience is being sustainable. In the past, when we talked about sustainability, it was easily understood as a philosophy, a moral stance, or a compliance cost. When the economy is good and policy support is strong, everyone is willing to talk about it. Once economic pressure, elections, geopolitical conflicts, or trade barriers arise, sustainability tends to be pushed to the back. Enhancing resilience, however, reflects your ability to respond to various frequent risks. For example, floods, heat waves, supply chain disruptions, tariff walls, carbon border taxes, community opposition, and regulatory fragmentation—these are not value issues; they are operational and financial issues. You can negotiate over sustainability, but you cannot say no to addressing the various risks above. Therefore, the real breakthrough for global sustainable transformation today should be reframing sustainability from doing good to surviving, lasting long, and withstanding shocks. For an enterprise to enhance supply chain resilience, it must know where its tier-one, tier-two, and tier-three suppliers are, which links concentrate carbon emissions, where labor risks lie, and where it is most vulnerable to geopolitical conflicts. For a city to enhance resilience, it must address energy, water, transportation, power grids, and community governance. These measures themselves are sustainable management. Take one example: due to geopolitical issues and other factors, Chinese clean technology going overseas has encountered a series of difficulties, including tariff barriers, the EU Carbon Border Adjustment Mechanism, battery passports, localization, and various other requirements. Many failed cases of companies investing overseas also show that poor supply chain governance is not a soft issue—it directly causes production stoppages, fines, and losses to brand and stock price. So enhancing resilience is not a question of whether companies are willing; it is something they must do. This is also why I believe the resilience framework is more politically operable. You do not need to persuade the board to pursue sustainability for moral reasons; you only need to ask: if the EU Carbon Border Adjustment Mechanism charges a carbon tax of 85-90 euros per ton, what is your cost? If the US energy storage battery tariff rises from 40% to 80%, can you still enter the market? If community protests delay factory construction by two years, what is your return on investment? These questions are understandable to management, and the board must answer them. Once sustainability indicators become the decision-making basis for these questions, they are no longer reports—they are management. So the most core lever is resilience. With resilience, there is sustainability. Turning sustainability from innovation into daily routine does not rely on more slogans, but on making every organization answer a harder question: if the next risk comes, can you withstand it? If you can, you are sustainable.

SINA Finance: Large models and AI technology are rapidly penetrating scenarios such as carbon accounting, climate risk prediction, urban resource scheduling, and corporate ESG data governance. Based on your research in sustainable quantification and indicators, what irreplaceable roles can AI play in sustainable development? At the same time, how should we avoid secondary sustainability problems brought by AI itself, such as computing energy consumption and data distortion?

Guo Dong: Sustainable management is essentially a management concept, and the core of management is measurement. Without measurement, there is no management; without credible measurement, there is no effective management. AI's contribution in scenarios such as carbon accounting, climate risk prediction, and ESG data governance lies in its ability to make many things that are difficult to quantify quantifiable, trackable, and comparable. For example, AI can integrate satellite remote sensing data and supply chain transaction data to automatically calculate a company's Scope 3 emissions. But at the same time, we must see a more fundamental problem: no matter how powerful AI is, it must rely on effective data sources. Even the cleverest housewife cannot cook without rice, and the same applies to AI. In the sustainability field, especially in climate change, a major problem we face is the lack of timely and effective data, and even more so the lack of reliable historical data. Climate observation data was very sparse before the introduction of satellite measurement systems, especially before the mid-20th century, with large numbers of missing values unevenly distributed in time and space. For example, early land observations were extremely limited, while ocean grid data was relatively complete. But because ocean warming patterns differ from land, if AI applies ocean-dominated patterns to land, it will systematically push up land temperatures. Because the input data is incomplete, untimely, and of low quality, AI output will be distorted, or even nonsensical. In climate science, we have already found many AI outputs that appear credible but are actually vague, weakly evidenced, and disconnected from policy contexts. Large language models can quickly and cheaply generate inaccurate scientific content, creating an illusion of understanding and equating more output with cognitive progress. As for the secondary sustainability problems brought by AI itself, there has been a lot of discussion in the West recently. The most direct concern is electricity consumption and carbon emissions. Data center demand for electricity has already overloaded power grids in some regions, and its overall emissions last year were roughly equivalent to Argentina's. In addition, cooling water usage is enormous. I have seen projections that by 2030, AI data center water consumption will equal the basic domestic water needs of 1.3 billion people, with conflicts especially acute in arid regions. There are also issues such as land occupation, exacerbated urban heat island effects, hardware manufacturing and electronic waste, and environmental injustice caused by the concentration of impacts in communities where data centers are located. Although some argue that AI can ultimately help reduce emissions through grid optimization, climate modeling, and waste heat utilization, at least for now there is broad consensus that efficiency gains from AI alone are difficult to offset its rapidly growing resource demand. Of course, AI itself is still evolving rapidly, and it is still hard to fully predict what form it will ultimately take, especially in applications across industries. Today we see large language models and generative AI; tomorrow it may be systems with completely different architectures, and application scenarios may far exceed our current imagination. Therefore, sustainable governance of AI cannot focus only on the current technological form; it must have a dynamic and highly adaptive framework.

SINA Finance: You have been engaged in sustainability research for many years and have witnessed the entire process of this field moving from a marginal topic to global consensus. Looking back from today, what change has impressed you most personally? Whether in research paradigms, policy environments, industry practices, or public awareness, which shifts have left the deepest impression on you?

Guo Dong: When I first entered this field in 2013, sustainability was mostly discussed by environmental scientists and social activists. The business community thought it was charity work, and the policy community thought it was the icing on the cake. The change that has impressed me most is this: ten years ago, when I went to give lectures in China, most of the time had to be used to persuade students to care about sustainability and to prove it was relevant to finance, operations, and strategy; in recent years, the focus of everyone's concern has shifted from why do it to how to do it. The research paradigm has also moved from describing problems to measuring them. Ten years ago, when we discussed sustainability, we talked more about what should be done; now, when we discuss sustainability, we talk more about how to measure it. The most fundamental driving force behind this shift is not moral awakening, but changed constraints. Policy language may swing back and forth depending on the region, but the underlying economic logic has not changed. Floods, supply chain disruptions, community opposition, and regulatory changes are not abstract sustainability concepts—they are concrete operational and financial problems.

SINA Finance: You have long shuttled between China and the United States, deeply engaged in the international academic frontier while also continuously following sustainable practices of Chinese cities and enterprises. Under this dual perspective, what special feelings or observations do you have in the sustainability field?

Guo Dong: The sustainable practices of China and the United States are more complex than they appear on the surface. First is a difference in context. In the West, especially in the United States, when people talk about sustainability, they generally mean sustainability, mainly environmental sustainability. In developing countries, however, sustainability is often closely tied to economic and social development—it is a more comprehensive concept, namely what the United Nations calls sustainable development. This is not a question of who is right or wrong, but a difference in focus brought about by different stages of development. My research on China has from the beginning attempted to unify economic development, environment, and social livelihood within one framework, precisely because in the Chinese context, sustainability detached from development is unrealistic. Second is the difference in driving forces. In the United States, companies often play a leading role in sustainable transformation. In China, the government plays the main driving role. But one thing is common: people are always the original driving force of change. In the United States, consumers often demand that companies adopt more humane and environmentally friendly production and management models. In China, the government's early motivation for implementing stricter environmental policies also came from public dissatisfaction with air pollution. Third is capability complementarity. China has stronger capacity in resource mobilization and large-scale climate-resilient infrastructure construction, while the United States has a more mature climate governance and response system. Against the current backdrop of geopolitical conflict, addressing climate change and environmental protection is already one of the few areas where China and the United States can carry out pragmatic cooperation. In fact, sustainable practices on both sides are not a question of who learns from whom, but of each finding the optimal solution under their own constraints. Constraints are usually the original driving force of innovation. The United States is now reversing course on sustainability issues, but companies have not slowed the pace of sustainable transformation. In fact, I increasingly feel that resilience is a common language. Defining sustainability as the enhancement of corporate resilience fits any political context. For example, for Chinese clean technology companies going overseas, the real test is not selling products, but how to embed themselves in local supply chains, meet local compliance and labor standards, manage community relations well, and at the same time control costs. More and more companies, against the backdrop of intense domestic competition, hope to expand into overseas markets, but for overseas business to be sustainable, going global must shift from simply exporting products to exporting capabilities and strengthening cooperation with local stakeholders.

SINA Finance: Your new book, Sustainable Indicators and Management: From Innovation to Daily Routine, has just been released. The phrase from innovation to daily routine in the title is quite profound and distinguishes it from books on the market that focus on policy innovation and theoretical frameworks. Could you outline the most core viewpoints of the book? What long-neglected blind spots in the current field of sustainable management does this book hope to address?

Guo Dong: Sustainable management is at the frontier of management theory development. Combined with what I said above, what sustainability needs to solve now is the question of how to do it. Therefore, the blind spot this book wants to fill is the last mile of sustainability moving from compliance rhetoric to management tool. People have talked a lot about the indicators sustainability should have, but very little about how these indicators should truly enter the daily decision-making of enterprises. In recent years, sustainability-related indicators have become increasingly refined. Initially, they were designed to address environmental issues such as greenhouse gas emissions, and now they also cover dimensions such as organizational governance, community benefits, and employment practices. The current problem is that a large number of indicators remain at the disclosure and compliance level and have not yet been embedded in organizational decision-making processes, budget allocation, and performance assessment. In other words, the indicators are innovation, but they have not become daily routine. We wrote this book for management practitioners, not for theorists. Therefore, what this book aims to do is help management open up the path from innovation to daily routine, and it contains several core viewpoints: First, sustainability is a management concept—a means, not an end. This means sustainable management is not a separate system built from scratch, but something that must be embedded in the existing management architecture. Second, the value of indicators lies not in reporting, but in management. We can use these indicators to track and advance progress on environmental, social, and business goals, but only when sustainability indicators enter daily decisions—such as investment evaluation, supply chain selection, and talent recruitment—will they truly generate management value. Third, the key to moving from innovation to daily routine is making sustainable management a regular component of organizational management. This cannot be achieved through a single strategy launch; it requires institutional design, process reengineering, and continuous measurement feedback. This is also the meaning of the title From Innovation to Daily Routine: sustainability should no longer be a one-time strategy launch, but should become a management action that the organization performs every day.

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