The conversation around artificial intelligence is rapidly shifting from theoretical breakthroughs to practical, scalable implementation. The central question is no longer “What can AI do?” but “How do we build the systems to make AI work for everyone?” This was the core theme at the 2026 Jiu Xian Qiao Forum in Beijing, where industry leaders gathered to chart a new course for AI-driven urban and industrial development.
A key announcement was the launch of Spark AI Cloud 2.0 by Beidian Digital Intelligence (BDI). This platform represents a significant evolution from a mere computing resource into a full-stack AI production system. Its goal is to tackle the most persistent barriers to enterprise AI adoption: complex deployment, high costs, and difficulties in replicating successful pilots. By integrating the “Forward AIOS” and “New Sky AgentOS,” the system packages the entire data-computing-model-application pipeline into a standardized, scenario-ready capability.
From MaaS to TaaS: The New Paradigm for AI Infrastructure
The forum highlighted a fundamental shift in how we measure AI progress. As noted by Zheng Weimin, academician of the Chinese Academy of Engineering, the industry’s focus is moving from simply amassing computing power (MaaS – Model as a Service) to optimizing the production of intelligence itself (TaaS – Token as a Service).
“With the arrival of the Agent era, the Token has become the unit of measurement for intelligence,” Zheng stated. “The competition has shifted from ‘comparing the scale of computing clusters’ to ‘comparing the production efficiency of Tokens per watt.'”
This TaaS paradigm is crucial for the scalable deployment of AI agents. It envisions a future where intelligent services are as reliably provisioned as electricity or water, making advanced AI accessible and affordable for widespread industrial and civic use.
A New Yardstick: The China City AI Index Report
To guide this complex transition, the forum saw the release of the inaugural China City AI Index Report. Developed by Tsinghua University, Shanghai Securities News, and BDI’s research institute, this report establishes a scientific framework to evaluate AI maturity across Chinese cities.
The report moves beyond a one-size-fits-all approach, categorizing cities into a three-tier gradient: Leading, Dynamic, and Potential. It assesses them across four core dimensions:
Industrial Development: AI’s integration and value creation within local economies.
Technological Innovation: The strength of the local R&D and talent ecosystem.
Public Service: The application of AI in healthcare, education, and governance.
Governance Environment: The policy and regulatory landscape supporting AI.
“The goal is not just to rank cities, but to help each one identify its unique advantages and a differentiated development path,” explained Gao Yuning, Vice Dean of Tsinghua University’s School of Public Policy and Management. This diagnostic tool is intended to help municipalities avoid redundant infrastructure investments and instead focus on AI applications that leverage local industrial strengths and address specific civic needs.
Building the Foundation: Spark AI Cloud 2.0 in Action
Spark AI Cloud 2.0 is positioned as the “new foundation” to operationalize the insights from the City AI Index. BDI’s CTO, Xie Dong, emphasized that the true sign of AI’s maturation is the lowering of barriers to entry.
“The hallmark of AI entering a stage of scale is the reduction of the usage threshold—enabling enterprises to leverage AI at lower cost and in simpler ways, transforming data into sustained productivity,” Xie said.
The platform’s “One Foundation, Two Breakthroughs” strategy outlines its dual focus:
- Empowering Industrial Scenarios: Driving growth models in sectors like manufacturing, cultural tourism, and retail.
- Enhancing Public Services: Improving capabilities in healthcare, government administration, and education.
By providing a standardized yet flexible system, BDI aims to move AI from isolated pilot projects to repeatable, large-scale production lines for intelligence, accelerating the development of what China terms “new quality productive forces.”
Taking it Nationwide: The “AI China Tour” and Innovation Districts
To propagate this new model of AI-powered urban development, the forum launched the “AI China Tour” initiative. This program, a collaboration between Shanghai Securities News and BDI, will dispatch teams of experts to work directly with local governments. The approach is “one location, one strategy; one industry, one policy,” ensuring solutions are tailored to local conditions rather than imposed from the top down.
Concurrently, Beijing is advancing its ambition to become a “global AI first city” through the creation of specialized AI Innovation Districts. The forum announced the launch of the “Optical Intelligence Space” in the Chaoyang district and the formation of an industrial alliance to support it. These districts are designed as integrated ecosystems, combining next-generation computing infrastructure with deep industry applications to foster new business models and accelerate scene-based innovation.
The Path Forward: Differentiation Over Standardization
A central conclusion from the forum’s expert discussions was the critical need for differentiated AI development strategies. The era of every city building identical computing centers and competing for the same tech companies is over. The new phase of competition is about practical, scene-driven落地 (luòdì – landing/implementation).
Cities must focus on their unique industrial heritage and public service demands. The future lies not in hardware alone, but in cultivating vibrant data governance practices, Token economies for agentic services, and cross-regional AI collaboration networks. The goal is to transform AI from a purchased technology into an endogenous driver of high-quality urban growth.
The launch of Spark AI Cloud 2.0, coupled with the new City AI Index and nationwide initiatives, signals a pivotal moment. It reflects a broader industry transition from building isolated AI models to engineering the complete, scalable systems required to weave artificial intelligence into the very fabric of our cities and industries. The race is no longer just about who has the smartest model, but who can build the most intelligent and inclusive systems for the future.
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