The 2026 Sustainable Global Leaders Conference returns to the banks of Shanghai's Huangpu River from October 20 to 22. Nobel and Turing Award laureates will take the stage to discuss the future and trends of technology, and the viral professors who "rescue" people from anxiety and involution-era pressures — Macfarlane and Xiang Biao — will hold a live dialogue. Seats are limited, so those who hesitate may miss out.
At the 2026 Bund Summit, the influence of artificial intelligence (AI) ran through every kind of economic and market topic, including how AI affects the macroeconomy, global central banks, AI debt financing risks, and AI financial governance.
The Impact of AI on Global Central Banks
At the roundtable titled "Central Banks in Transition: Mandates, Markets and Macroprudential Risks," the impact of AI on the macroeconomy — and how it might consequently shape central bank decisions — became another focal point of discussion, alongside central bank independence. Jacob A. Frenkel, former Governor of the Bank of Israel, Honorary Chairman of the G30, and Chairman of the Frenkel-Zuckerman Institute for Global Economics, argued that AI's impact on supply could be significant but would not materialize in the short term. At the same time, asset valuations based on future expectations are already pulling demand forward. Whether AI ultimately leans toward pushing inflation up or holding it down needs to be assessed within this framework. As for claims that attribute global economic resilience to AI, he said that before the underlying mechanisms are clearly understood, it would be unwise to rely too heavily on that explanation. Donald Kohn, former Vice Chairman of the Federal Reserve, said the AI investment boom is boosting demand before it affects supply, adding to inflationary pressure. Meanwhile, the U.S. labor market is performing steadily, but wage growth is not high, and workers' concerns about AI may be suppressing their demands for pay raises. Philip R. Lane, Chief Economist of the European Central Bank, noted that AI's impact on global supply chains has supported the euro area's trade this year and also stimulated its economy, though to a lesser degree than in the United States. Masaaki Shirakawa, former Governor of the Bank of Japan, suggested that rather than directly assessing AI's impact on the economy and central bank policy, it is more important to focus on AI's impact on society. He recalled that when the internet emerged thirty years ago, there was optimistic belief that it would improve people's livelihoods, but various negative effects subsequently emerged. He believes it is necessary to pay attention to how AI affects people's livelihoods, because that relates to the operation of monetary policy and financial stability measures.
AI Debt Financing Risks
In a dialogue between Robert Rubin, member of the Bund Summit's International Advisory Board, 70th U.S. Secretary of the Treasury, and Honorary Co-Chair of the Council on Foreign Relations, and Huang Yiping, Dean of the National School of Development at Peking University, on AI's impact on the labor market, Huang raised the risk of "circular commitments" in AI investment — that is, large technology companies make massive procurement commitments, upstream suppliers expand sharply in response, and once those procurement commitments cannot be fulfilled for some reason, it could trigger a sharp market adjustment. In response, Rubin said the U.S. banking system is generally healthy, large banks lending to AI-related businesses are well capitalized, and regional banks have largely stayed out of this area, while non-bank financial institutions have some problems. He believes individual companies may run into trouble because of loopholes in AI investment, but the probability of triggering a systemic financial crisis is extremely low. "Everything related to AI comes with enormous uncertainty. Our economy and markets have always had ups and downs — that is their nature," he also acknowledged. Klaas Knot, former Governor of De Nederlandsche Bank, was more cautious. He said that according to the data he has, about one-third of the AI investment boom comes from debt financing, and off-balance-sheet commitments often mean the true share could be even higher. Therefore, the market should not underestimate the possibility of a significant adjustment, especially since U.S. consumption is relatively sensitive to the wealth effect, meaning an adjustment could come faster and have broader effects.
Financial Regulation of AI
As AI increasingly permeates every aspect of the economy and markets, financial regulation of AI has become a topic of growing concern. At the roundtable titled "AI Governance in Finance: Key Issues and Feasible Paths," Zhang Wencai, Managing Director and Chief Administration Officer of the World Bank, said a World Bank survey shows that only 11% of financial regulators in emerging markets are using AI regulatory tools, and about half say they lack sufficient personnel and tools for effective supervision. There are two speeds of regulatory capacity across economies: some are already at the frontier and can use AI technology to prevent and detect fraud, while others have no tools at all. At the same time, he emphasized that the field also faces excessive reliance on a small number of cloud service providers and model providers. He offered three recommendations: first, strengthen the foundation by learning from rather than reinventing. Countries with limited capacity can draw on existing international practices and guidelines, integrate digital identity into data protection and payment systems, and direct limited resources toward the highest-risk areas. Second, help regulators use AI and regulate AI, which requires staff who know how to use AI and more interconnected data. Third, financial institutions must still be held accountable for AI decisions, and institutions handling cybersecurity and data protection should sit in the same room to coordinate, sharing regulatory tools, test results, and early warnings across borders. Zhang also added that AI technology can expand financial inclusion, but it must be designed in from the start — inclusion will not happen automatically. He warned against conflating the two: some people receive digital loans yet remain worse off than before; if models are biased, rules are unclear, or users cannot challenge decisions, and if data does not reflect the real lives of women and informal workers, these groups will lose out. In the World Bank survey, 59% of financial regulators in emerging markets listed fraud and scams as high risks facing consumers. He proposed three safeguards: strengthen the foundations of identity, interoperable payments, and data governance; look at outcomes rather than just models, with regulators asking who was approved, who was rejected, and who pays higher costs, and explaining decisions in plain language while giving users simple ways to appeal; and protect choice and competition, preventing a small number of platforms from controlling data, distribution, and tools. Lorenzo Bini Smaghi, Chairman of the European 50 Group, offered a European regulatory perspective. Compared with other regions and major economies around the world, Europe has been ahead on AI regulation, and is seen as setting regulatory rules first and developing AI afterward. Asked whether Europe regulates AI excessively, Bini Smaghi said he interviewed Mistral, Europe's largest AI company, and it believed Europe's current regulation could be improved but was not the biggest problem. The real challenge is scale — how to secure enough capital while continuing to operate in Europe, and how to access customer markets including public procurement.
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