On 19 July, the WAIC 2026 Ecosystem Forum on the Development of the Intelligent Economy was held in Meeting Room 2 of the Shanghai World Expo Exhibition and Convention Centre. The forum was hosted by Shanghai University of Finance and Economics (SUFE) and jointly organised by the Digital Economy Research Institute of SUFE together with multiple academic think tanks, enterprises and media outlets. With 'paradigm shift, chain restructuring, and ecosystem co-creation' as its core theme, the forum brought together distinguished guests from government, industry, academia and research to discuss new paradigms of the intelligent economy, digital-intelligent finance and economics, talent cultivation, AI governance, and to launch a number of outcomes.
Keynote Speech: The Paradigm Shift in the Intelligent Economy
Paradigm Shift One: AI Is Moving from 'Tool Application' to 'Paradigm Change'
Liu Yanchun, President of Shanghai University of Finance and Economics, delivered a keynote speech titled 'AI and the New Form of the Intelligent Economy from an Economic Perspective'. He pointed out that a new form of the intelligent economy has already emerged, and AI is transitioning from 'tool application' to a 'paradigm change' that reshapes the fundamental logic of the economy. AI has driven foreign trade growth beyond expectations, forming a core component of the 'China Shock 2.0' and the 'China Opportunity 2.0'; the current K-shaped recovery is a product of the impact of AI, as well as the result of multiple factors including technological and industrial revolutions, profound adjustments in the real estate sector, and structural changes both globally and in China. He cautioned against both undue optimism and pessimism regarding short-term impacts due to the 'Solow Paradox' and the 'J-curve' effect of AI implementation; in the face of challenges related to employment and distribution, he explored five widely discussed global topics, including digital taxes and universal basic income. Finally, he put forward three conclusions: first, the new form of the AI economy and the intelligent economy has fully established its role as a key new driving force, but the economics of AI and digital-intelligent economics have not yet begun; second, using traditional analytical frameworks makes it difficult to uncover the essence and laws of the AI economy, which may lead to unnecessary errors and confusion; third, AI remains a development model that has only just begun, and its developmental path and impacts are highly uncertain. We need to actively embrace and prudently approach it, but it is by no means a re-enactment of Luddism.
Shrikanth Narayanan, Academician of the US National Academy of Engineering, delivered a keynote speech titled 'The Frontier of Human-Centered AI for the Intelligent Economy'. He pointed out that the frontier of AI has never been solely about 'what machines can do', but rather about what we choose to let them do, and how well we design it for the people who ultimately remain in control. Generative AI has currently been adopted by 53% of the global population, yet 95% of enterprise pilots have not delivered measurable outcomes. The bottleneck lies not in the algorithm but in human acceptance and organisational adaptation; the speed of technology adoption is unprecedented, but the realisation of value lags far behind, and this gap is precisely where 'Human-Centered AI' comes into play. The speech unfolded its framework around three pillars—'trust and transparency, agency and control, augmentation rather than replacement'—and used future education, health, and work as examples to demonstrate that only by placing humans at the centre of design can AI truly translate into social value; and that net gains are not automatic but a 'design decision'.
The forum was chaired by Liu Liya, Vice President of Shanghai University of Finance and Economics.
Big Talk: 'Breaking Boundaries and Reshaping – Four Questions on Education in the AI Era' was a roundtable discussion on the new digital-intelligent finance, chaired by Gao Hongbing, Dean of the Digital Economy Research Institute of Shanghai University of Finance and Economics. He raised four first-principle questions on education in the AI era: 'the misalignment between first principles and the definition of talent', 'breaking boundaries and practical training in cultivation pathways', 'reshaping the learning paradigm', and 'the identity and rights system of cross-agents'. Liu Yuanchun, President of Shanghai University of Finance and Economics, Zhang Weizhong, Chairman of Shanghai Pudong Development Bank, and Wang Minwen, Chairman of Lion Microelectronics, appeared on the same stage to present different perspectives from the technology, finance, and education sectors on the cultivation of finance talents in the AI era.
Industry perspective: "Not understanding the logic of AI is like using an abacus in the electronic age." Taking the semiconductor industry as an example, Wang Minwen pointed out that digital literacy for all has become an essential requirement. For finance students, not grasping the basic logic of AI is 'like an accountant using an abacus entering the electronic age.' Enterprises urgently need interdisciplinary talents who 'understand AI and can take action'—currently, such talents cannot be cultivated in traditional classrooms but must be honed on real production lines. What enterprises need are practical problem-solvers. Financial perspective: "What is scarce are those who can define problems and master tools." From the financial industry's point of view, Zhang Weizhong noted that what will be scarce in the future will no longer be people who can complete tasks, but those who can ask the right questions and skillfully use intelligent tools. Employees most need a 'human-machine collaboration' mindset, rather than simply taking more AI courses. The ability to judge trends, demands, risks, and responsibilities is a foundational capability that AI cannot replace or learn. Educational perspective: "Cultivating those who define problems, not tool users." Responding from the supply side of education, Liu Yuanchun pointed out that the first principle of universities is shifting from 'cultivating those who possess knowledge' to 'cultivating those who define problems, master tools, and create value.' Shanghai University of Finance and Economics is breaking down barriers with its 'Digital-Intelligent New Finance' initiative, implementing 'industry-education integration' by bringing classrooms into the frontlines of industry, and establishing a dual-mentor collaborative education mechanism between academia and industry. In the future, universities will shift from teaching 'knowledge' to teaching 'how to ask questions.' How students learn is 100 times more important than what they learn. The cultivation of new finance professionals requires a system that integrates 'new liberal arts + new engineering.' Though the four perspectives on education may seem divergent, they actually point to one certainty in the AI era: 'change' itself. Finance professionals need to 'harness AI rather than be replaced.' 'Digital-Intelligent New Finance' is a mutual commitment between Shanghai University of Finance and Economics and the industry.
Keynote Speech: From Governance Leadership to Global Ecosystem
Xue Hui, Executive Vice President of China Dalian Executive Leadership Academy, delivered a keynote speech titled "Forging AI Governance Leadership: Talent Cultivation and Industrial Ecosystem Development in the Era of Intelligent Transformation." He proposed that managers should possess four fundamental 'AI governance leadership capabilities': strategic judgement, professional competence, cross-border governance, and organisational transformation. He analysed the 'four-fold misalignment' between the 'exponential leap' of industrial intelligent transformation and the 'linear evolution' of talent, advocating for the construction of a new talent cultivation paradigm of the 'industrial ecosystem type.'
Qiu Da, Vice President of DingTalk, gave a keynote speech on "Beyond Models—Four Engineering Essentials for Enterprises to Effectively Use Agents," sharing that the four essentials for enterprises to make good use of Agents are Harness architecture, data preparation, Skills and MCP production, and permission and security design. He emphasised that 'currently, what is least lacking in the AI era are tools—the real shortage is the ability to think through the sequence clearly.'
Yang Haijun, Deputy Director of the Shanghai Municipal Party Committee Cyberspace Administration, delivered a keynote speech on 'The Development Environment of the Intelligent Economy – From the Perspective of AI Governance', analysing the balancing approach to the development of the intelligent economy from the perspective of AI governance. He proposed the dialectical view of 'promoting development through security, and promoting security through development', and outlined the cultivation of an environment for the development of the intelligent economy across five dimensions: professional services, constructive regulation, institutional supply, and others.
Gao Hongbing, Dean of the Digital Economy Research Institute at Shanghai University of Finance and Economics (SUFE), gave a speech titled 'AI Native: Global Ecosystem Evolution and Next-Generation Entrepreneurship'. He used four sets of data to define the landscape of AI development: 'ChatGPT has over 1 billion monthly active users, Claude Code has achieved an annualised revenue of USD 1 billion within six months, 80% of global venture capital in the first quarter flowed into AI, and China’s open-source model Hugging Face download share reached 41%, surpassing the United States for the first time.' He emphasised the foundational role of the MCP protocol as the 'USB-C' of the agent world, as well as China’s cycle of 'setting standards through open source and securing funding through IPOs'. He clearly pointed out that while the current development of artificial intelligence presents both bubbles and revolutions, the restructuring across four layers – entry points, protocols, payments, and business models – is already irreversible.
Key achievements in the practice of intelligent economy ecosystem construction were officially released.
SUFE
The final segment of the forum featured the collective release of five practical achievements in the construction of an intelligent economy ecosystem, covering multiple fields including financial data intelligence, digital-intelligent education assessment, AI talent cultivation, and industrial multi-agent systems, thereby translating consensus into action and crystallising ideas into tangible outcomes. Tang Pei, Senior AI Expert of the Government and Enterprise Business Division at Alibaba Cloud, unveiled Alibaba Cloud’s AI Talent Cultivation Product, designed to systematically deliver high-calibre AI professionals. Peng Yijie, Distinguished Chair Professor at Nanjing University and Director of the Institute of Complex Systems Management, introduced 'Qingtianshu' — an Industrial Multi-Agent Collaborative Decision-Making Platform that provides a technical foundation for multi-agent collaborative decision-making in smart factories. Zhang Liwen, Director of the AI Finance Development and Service Centre at Shanghai University of Finance and Economics (SUFE), launched FinCorpus, a Financial Data Intelligence Service Platform, and FinEval, a Financial Large Model Evaluation System, establishing a high-quality financial data foundation and a professional assessment benchmark. Zhao Lin, Dean of the School of Digital Economy at SUFE, presented a Service Sector Digital-Intelligent Cognition Assessment and Guidance System to help service industry professionals rapidly enhance their digital skills. Hu Yanping, Practice Professor at the Digital Economy Research Institute of SUFE, released an Education Decision-Making Research Large Model and Agent, focusing on the scientific governance and decision-making in education and providing technological support for the digital transformation of education. The forum concluded with the joint unveiling by SUFE and China Business Executives Academy, Dalian of the 'China Business Executives Academy, Dalian – Shanghai University of Finance and Economics Intelligent Economy Case Development Centre', as well as the presentation of industry mentor appointment letters to professional experts including Pan Bin, Qiu Da, Li Sheng, Du Wenwu, and Dai Zijun. This forum crystallised four core consensuses: first, the shift in paradigm — AI is rapidly reshaping the fundamental logic of the economy, yet research on 'AI Economics' has only just begun; second, the change in talent — the first principle of education is shifting towards 'cultivating those who define problems', with the 'new liberal arts + new engineering' approach reshaping the training model; third, the transformation in implementation — organisations need to possess both AI governance leadership and agent engineering capabilities, and the integration of industry and education must advance towards practical realisation; fourth, the evolution in ecosystem — adhering to 'promoting development through security', China is rising in the global AI landscape by 'setting standards through open source and securing resources through IPOs'. Looking ahead, SUFE will continue to advance the implementation of the 'Digital-Intelligent New Finance', contributing the 'SUFE Solution' to the high-quality development of the intelligent economy through deepened collaboration among government, industry, academia, and research. The Intelligent Economy Development Ecosystem Forum was hosted by SUFE, with multiple organisations co-organising and co-sponsoring.
