"Cities are far more than mere assemblies of steel, concrete, and roads; they are dynamic entities that constantly perceive, evolve, collaborate, and expand."

This sentiment perfectly encapsulated our experience at the Huawei Cloud INSPIRE Innovators Conference.

Several years ago, discussions around smart cities predominantly revolved around topics such as the migration of government services to the cloud, the implementation of one-stop online government services, the development of city brains, and the establishment of data platforms. At the "Advanced Public Cloud Industry Summit," buzzwords included large models, AI-native solutions, silicon-based intelligence hubs, and urban super-intelligent agents.

As Zhou Yuefeng, Director of Huawei and CEO of Huawei Cloud, highlighted in his speech: "The rapid evolution of AI technology and the exponential growth of model parameters make public clouds, with their advantages in centralized infrastructure, highly compatible with the current trend of large-scale and efficient development. Public clouds encompass a variety of models, including enterprise alliance sharing and government exclusives, and represent the optimal infrastructure for small and medium-sized enterprises and research institutions to access advanced computing power."

In the realm of smart cities, AI CITY does not materialize out of thin air; it necessitates a continuous influx of intelligence through a 'silicon-based intelligence hub,' enabling computing power, data, models, applications, and security to become integral public capabilities of the city, akin to 'water and electricity.'

Huawei Cloud poses the question and offers the solution.

The evolution of smart cities can be succinctly summarized in three stages: connection, convergence, and visualization.

During the informatization phase, the emphasis was on digitizing business processes, with numerous government processes, public services, and departmental systems transitioning from offline to online.

In the digitalization phase, the focus shifted to data convergence and collaboration, with data from disparate departments and systems gradually becoming interconnected.

In the early stages of intelligence, situational awareness and decision support were achieved through algorithms and models. For instance, the 'city brain' enables managers to monitor real-time traffic congestion, environmental changes, emergency risks, public services, and other city events.

However, the evolution of smart cities is far from complete: they can 'identify problems' but may not automatically comprehend them; they can display status but may not proactively assign tasks; they can assist in decision-making but may not collaborate with systems to execute tasks.

The year 2026 is poised to be a pivotal moment in the history of smart cities.

Large models have endowed AI with understanding and generation capabilities, while agents have further equipped AI with task execution abilities. Agents can not only answer questions but also comprehend intentions, plan paths, access data, collaborate with systems, and autonomously complete a series of complex tasks.

In the current phase of smart cities, humans are required to identify problems, determine causes, assign tasks, and monitor results. In contrast, AI CITY, powered by large models and agents, allows humans to set goals while intelligent agents autonomously analyze, decide, and execute.

A prime example is the urban super-intelligent agent in Karamay.

Rewinding to 2012, Huawei's inaugural global government cloud landed in Karamay, marking the commencement of the industrial city's digital and intelligent transformation journey. Over the past 13 years, Karamay has undergone three levels of transformation—digitization, digital intelligence, and data governance—and has transitioned from 'problem identification' to 'problem resolution' through the full-stack capabilities of the 'urban super-intelligent agent,' encompassing perception and interaction, cognition and decision-making, and autonomy and evolution.

For instance, in developing government applications, the traditional approach took 2 to 3 months from project initiation to delivery. However, leveraging Huawei Cloud CodeArts and full-stack government cloud services, the development cycle has been reduced to just half a month. Currently, Karamay has implemented multiple mature government intelligent agents, significantly enhancing the city's comprehensive operational efficiency and delivering remarkable results in public services, economic development, and ecological construction.

Another example is the deployment of intelligent agents, where ecosystem partners can seamlessly integrate through the A2A protocol, fostering a new ecosystem of open and evolving intelligent agents in Karamay.

In contrast to the 'city brain': following an emergency event, the city brain can merely present data, while the urban super-intelligent agent can further comprehend the nature of the event, correlate historical data, determine involved departments, break down execution tasks, dispatch relevant agents, and accumulate disposal results for reuse in similar future scenarios.

While many cities grapple with issues such as inconsistent technical frameworks, severe data silos, difficulties in coordinating computing power and algorithms, and poor adaptation in scenario implementation, why has Karamay, known as the 'Gobi Oil City,' achieved visible data governance success?

The answer is straightforward: Karamay is the pioneer in implementing 'AI CITY 2.0.'

In the realm of Token Economics, the most crucial aspect is 'how to efficiently produce tokens.' For a city, the prerequisite for intelligent transformation across all industries is how to connect, utilize, and operate AI at lower costs and higher efficiency.

At the Huawei Cloud INSPIRE Innovators Conference, the new Agentic Infra paradigm was officially unveiled: 'Efficient Token Factory + Continuous Learning + Integrated General and Intelligent Scheduling + Secure Autonomy.' Concurrently, a series of Agentic Infra products were introduced, including the AICS Lingqu Intelligent Computing Cluster, AMS Agentic Memory Storage Solution, CCE VolcanoNext Integrated General and Intelligent Scheduling Engine, and the secure and autonomous Agent operating environment, AgentSphere, to assist industries in creating a 'silicon-based intelligence hub' with coordinated software, hardware, and chips.

Among these, in the field of smart cities, the new Agentic Infra paradigm has profoundly influenced the construction of urban AI cloud services.

Hu Yuhai, President of Huawei Public Cloud, responded by stating that Huawei Cloud, with 'AI CITY' as its core concept, has collaborated with ecosystem partners to build a full-stack solution capability from AI infrastructure to intelligent agent applications. It unveiled the 1+2+3+N AI CITY reference architecture to facilitate cities in achieving comprehensive leaps in 'efficient governance, benefit to the public, and industry revitalization.'

'1' represents a set of AI infrastructure.

AI's empowerment of cities has rapidly extended from traditional government services to public services. Hu Yuhai specifically mentioned the deployment model of 'one cloud, two domains,' which coordinates resource pools in the government domain and public domain to ensure unified scheduling and efficient collaboration of city-level resources.

'2' refers to two AI innovation engines.

Model as a Service lowers the barriers to model invocation, adaptation, and continuous iteration; Data as a Service transforms data scattered across different departments, systems, and levels into callable, trainable, and serviceable city assets after governance.

'3' denotes three AI enablement platforms.

AgentArts, for developing and running enterprise-level and government-level intelligent agents; CodeArts, enabling application development to transition from manual coding to AI-assisted and automated closed-loop development; and DataArts, transforming urban data from raw resources into governable, callable, and decision-making assets, aiding various departments in swiftly implementing intelligent agent applications for specific scenarios.

'N' signifies N AI intelligent scenarios.

Huawei Cloud, in collaboration with ecosystem partners, has accumulated 'N out-of-the-box' best practices, encompassing expert capabilities in government, public services, and industries, as well as replicable processes, tools, and templates. This enables cities to avoid starting from scratch and quickly replicate, deploy, and achieve results in scenarios such as government services, urban governance, public services, and industrial development.

Additionally, a full-stack proactive defense system is in place, including role-based authorization, identifying malicious tasks, blocking destructive behaviors, and full-link monitoring of agent malicious behaviors, achieving a shift from passive 'unplugging to stop losses' to proactive 'prevention and control,' ensuring the secure and reliable operation of intelligent agent applications.

To draw an analogy, the '1+2+3+N' AI CITY 2.0 reference architecture is akin to an urban-level 'AI operating system,' addressing a series of issues that impede AI implementation at the foundational level, such as computing power, data, and scenarios. It enables every city to construct an AI CITY based on its unique strengths, continuously injecting new vitality into industrial upgrading, public service enhancement, and urban governance.

The rise or fall of a city hinges on its ability to enhance governance efficiency, service capabilities, and industrial vitality.

The most significant distinction between AI CITY and traditional smart cities is that AI CITY does not focus on functional upgrades of individual systems or treat AI as a mere add-on tool. Instead, it organizes AI infrastructure, data services, model capabilities, intelligent agent platforms, and scenario practices, allowing AI to truly permeate the mainstream of urban operations and transform into tangible new quality productive forces.

The case of Karamay mentioned earlier is not an isolated instance; an increasing number of cities are exploring diversified paths based on the AI CITY 2.0 reference architecture.

In Shenzhen, Guangdong, AI has become the quintessential tool for benefiting the public.

Based on the successful practice of 'Citizen Cloud,' Longgang District, Shenzhen, has comprehensively upgraded digital public services, providing each household with 4T of exclusive digital living space and gradually implementing personalized AI applications such as 'private doctors,' 'study companions,' and 'service assistants.' This facilitates Longgang's leap from 'digital empowerment of life' to 'digital is life,' ensuring that 4.8 million residents can step into the new digital world equally, calmly, and with a sense of gain.

In government applications, the Shen Xiaoi government AI assistant has organized knowledge graphs of over 2 million words in six high-frequency areas such as business establishment. By innovating a 'general-specialized combination' multi-agent collaborative elastic scheduling technology, it achieves a 97.7% response rate and a 94.3% accuracy rate for government questions, becoming an 'efficient and reliable' government intelligent customer service.

In Wuhan, Hubei, AI is transforming the lives of every citizen.

As early as 2021, Wuhan collaborated with Huawei to build the nation's first 'urban cloud,' providing a 'intelligence hub' for intelligent transformation across all industries.

Taking smart healthcare as an example, by constructing a municipal imaging data sharing center, 'Wuhan Cloud' has achieved cloud-based convergence and cross-institutional sharing of imaging data, significantly optimizing patients' healthcare experiences. As of early April 2026, through city-wide imaging data access and mutual recognition, the Wuhan medical insurance imaging cloud is expected to help citizens save approximately 1.2 billion yuan in inspection costs annually.

In Wuxi, Jiangsu, AI exploration is delving into the core of industries.

When surging AI computing power is readily accessible, AI CITY is not merely a carrier for AI applications but can also serve as an 'incubator' for industrial intelligence.

As a manufacturing hub, Wuxi focuses on the potential sector of 'industrial embodied intelligence,' building a 'city of data and scenarios.' It pioneered the 'data spectrum theory,' systematically conducting large-scale collection of three types of 'data crude oil'—real machine, simulation, and human-like data—covering over 300 industrial scenarios.

Relying on the Huawei Cloudrobo platform, Wuxi has built its data pipeline, completing the entire model infrastructure process from 'crude oil extraction' to 'refining.' Simultaneously, it innovates the city partner mechanism, promoting data rights confirmation, assetization, and capital closure, establishing the Wuxi paradigm of 'data-driven production, scenario-nurtured production, and finance-catalyzed production,' and laying a solid digital foundation for China's industrial embodied intelligence.

From Karamay's 'efficient governance' to Shenzhen Longgang and Wuhan's 'benefit to the public,' and then to Wuxi's 'industry revitalization,' AI CITY has validated a clear path: urban intelligence is not merely about constructing a few systems or launching a few AI applications but embedding AI capabilities into the key processes of urban governance, public services, and industrial development, with AI infrastructure as the foundation and intelligent agents as the driving force.

Broadening our outlook, Huawei Cloud's AI CITY 2.0 reference framework has established a comprehensive approach for intelligent transformation that is adaptable to the majority of cities. This involves, initially, constructing a unified urban AI infrastructure; subsequently, reducing obstacles to innovation by means of innovation engines and enabling platforms; thoroughly integrating AI functionalities into governmental, public service, and industrial contexts; and finally, guaranteeing the extensive and enduring functionality of intelligent systems through robust governance measures.

The digitalization movement that took place a decade ago paved the way for cities to become visible, documented, and manageable. The ensuing surge in intelligence a decade later has further imbued cities with the capacities for comprehension, cooperation, and execution.

Cities like Karamay, Shenzhen, Wuhan, and Wuxi serve as prime examples, demonstrating that with an AI CITY digital and intelligent infrastructure—comprising urban AI clouds, model services, data services, and intelligent agent platforms—every city has the potential to organically foster novel business models aimed at efficient governance, public welfare, and industrial rejuvenation.

The AI CITY 2.0 reference framework transcends being a mere model practice tailored for a specific city; rather, it stands as a universal blueprint that can be applied to the digital and intelligent transformation endeavors of cities across the globe.