From October 21 to 23, 2025, the 2025 Shanghai Competitive Intelligence Forum (SCIF 2025) was successfully held in Shanghai. The forum, themed “Intelligence for Future Cities” brought together experts and scholars from various fields such as international organizations, research institutions, and industry to jointly explore the cutting-edge trends in urban governance and development in the new era. The event not only showcased applications of technologies such as artificial intelligence in city management but also focused on systematic enhancement of urban cognitive capabilities, emphasizing the profound value brought about by the integration of technology and decision-making mechanisms. Building an urban cognition system centered on technology and intelligence is becoming a key pathway to strengthen strategic capacities and sustainable competitiveness of cities. This article reviews the forum’s core topics and insights, offering an intelligence-driven
perspective to interpret the logic and trends of future urban development, providing useful ideas and references for city policymakers, researchers, and practitioners in related industries.

The rapid diffusion of digital technologies is profoundly transforming urban governance. Digital governments and smart cities have become central policy paradigms for improving administrative efficiency, rationalizing public service provision, and enhancing citizens’ quality of life. Digital government deploys big data, artificial intelligence (AI) and related tools to strengthen the efficiency and transparency of public services and promote the intelligent and evidence base of government decision-making, while smart cities integrate the Internet of Things (IoT), cloud computing and other advanced technologies to elevate the intelligent level in multiple fields, including urban infrastructure construction, traffic management and environment protection. To explore in depth how these technologies drive future urban governance, taking advantage of the opportunity of the 2025 Shanghai Competitive Intelligence Forum held in Shanghai in October, our magazine conducted an interview with Lee Sungho, the director of the AI and Big Data Laboratory at the Seoul Institute in South Korea, who was a guest at the forum. This interview systematically analyzes his assessment of digital government and smart city development in Seoul, and explores how AI and big data play a key role in enhancing urban governance capacities, optimizing public services and improving the quality of life for citizens, aiming to provide references for the digital transformation of governments in China and other countries. The edited interview transcript is presented below, with annotations added by the editors.

Mr. Rob van Kranenburg is a speaker at the “2025 Shanghai Competitive Intelligence Forum”. With his authorization, this article is written based on his speech and the content of his new book Statecraft and Policymaking in the Age of Digital Twins: Digital Democracy and the Internet of Things. Against the backdrop of the convergence of technologies such as the Internet of Things, artificial intelligence, and 6G communications, this article explores the profound transformation of contemporary urban governance from the “smart city” to the “wise city”. The article first analyzes how cities, in an environment where objects, machines, and artificial intelligence are deeply interconnected, can upgrade governance models by leveraging data perception and systemic decision-making. It then examines the dilemmas and challenges faced by social governance in today’s digitalization process—particularly the limitations of the Western “entrepreneurial government” model and its intrinsic association with the rise of populism. Finally, the article proposes a pathway for the evolution from an
“entrepreneurial government” toward a “co-creative ecosystem”, emphasizing a new governance paradigm centered on “event identity”, key value indicators (KVI) , and a polycentric governance architecture. The article argues that the future of urban governance is not merely a matter of technological integration but also a deep fusion of cognitive frameworks, institutional designs, and humanistic values. At its core is the construction of a systemic decision-making mechanism that is both responsive to real-time data and grounded in public rationality. This governance mindset offers new insights and reference points for research and practice in urban competitive intelligence: as cities and industries operate in increasingly technological and real-time modes, competitive intelligence must not only capture surface-level innovation trends but also penetrate the underlying logic of systemic transformation. It must not only analyze data but also understand the governance structures and social risks behind the data. Such systemic thinking will empower intelligence analysts to grasp the coupling relationship among information, power, and value in the technology driven city of the future, providing deeper cognitive support for strategic decision-making. It must be noted that the discussions in this article are based on the European context, and the relevant conclusions or viewpionts may have certain contextual limitations.

Cities serve as crucial strategic spaces for modern intelligence work. This study on programmable urban intelligence empowerment aims to deepen the understanding of intelligence service models and operational mechanisms within the context of emerging urban spatial forms, and offer theoretical support and practical insights for intelligence practices in the era of digital and intelligent urban governance and development. First, by integrating the programmable characteristics of cities with the digital development trends of intelligence work, the study systematically analyzes their coupling relationship and mutual needs. Second, it explores the highlights and leverage points, key areas and challenges of programmable urban intelligence empowerment, clarifying the underlying logic and strategic levers of such empowerment. Finally, it proposes practical paths from three dimensions of anchoring empowerment tasks, strengthening empowerment support, and cultivating empowerment ecosystem. The findings reveal that the practice of intelligence empowerment in programmable
cities can be advanced through multiple synchronous and asynchronous pathways “synch ronous + asynchronous” to anchor empowerment tasks; through combined technological and data-driven approaches “technology + data” to consolidate empowerment support; and through adaptive and reform-oriented measures “adaptation + reform” to nurture the empowerment ecosystem.

Amidst the global digital wave reshaping international trade patterns, cross-border e-commerce is undergoing a paradigm shift from factor-driven to innovation-driven development. This study employs Chinese cross-border e-commerce enterprises as research subjects, constructing a dynamic threshold evolution model grounded in self-organized criticality (SOC) theory to systematically unravel the nonlinear mechanisms through which industrial chain innovation element agglomeration enhances corporate competitiveness. Empirical findings reveal: (1) Cross-dimensional synergy of innovation elements within industrial chains significantly amplifies corporate competitiveness, demonstrating multiplier effects from deep integration of innovation chains and industrial chains; (2) Increased international network density as a moderating variable elevates marginal effects
of innovation element agglomeration, confirming globalization embeddedness as a catalyst for innovation diffusion; (3) Market access demonstrates significant dual threshold effects. When institutional barriers transcend the critical threshold, self-organized criticality evolution is triggered, resulting in exponential leaps in the impact of industrial chain innovation levels on corporate competitiveness. This research provides theoretical insights for cross-border e-commerce enterprises to overcome developmental bottlenecks.

In an era marked by global intensifying competition and rapid advances in digital and artificial intelligence technologies, provincial science technology information institutions must explore new development strategies. This research undertakes a comprehensive investigation of 30 provincial-level science and technology information institutions, systematically evaluates their data resource management, platform infrastructure development, and service implementation practices to diagnose existing barriers in the innovation and development process of provincial science and technology intelligence institutions. Drawing upon Qian Xuesen’s systematic science philosophy, the study formulates a “six-dimensional integrated” developmental architecture: multi-sourced data aggregation, intelligent service platform construction, diversified service content, personalized service provision, adaptive service modeling, and ecosystem-oriented system development, thereby establishes a holistic roadmap for institutional advancement in the digital and intelligent age.

The copyright compliance of training data for generative artificial intelligence represents a common challenge in global industrial governance. This paper takes the U.S. court rulings in the 2025 cases of Bartz v. Anthropic and Kadrey v. Meta as its starting point, employs a combination of case analysis and comparative legal research to systematically deconstruct the judicial application logic of the fair use doctrine in the context of generative artificial intelligence training data. The study finds that although the U.S. judicial practice acknowledges the rationality of using AI training data in individual cases, its adjudication highly depends on specific case facts, exhibiting significant characteristics of case-by-case discretion. Notably, judges have universally expressed profound concerns about potential market impacts in their rulings and have reserved room for adjustment in future jurisprudence at the legal theoretical level. This judicial model, characterized by the coexistence of limited exemptions and systematic uncertainties, provides an important reference for the governance of artificial intelligence data.