AI City plays a key role in the next phase of Taiwan’s AI development. Following Taiwan's proven track record in AI hardware component manufacturing and information system parts, our next initiative is to demonstrate how cities can become real-world platforms for AI innovation. Under a sovereign AI framework, AI City brings together hardware manufacturers and software companies to create a new AI ecosystem that drives both urban transformation and industrial upgrading.
This vision will be showcased at the 2026 Smart City Summit & Expo and Net Zero City Expo (SCSE 2026), taking place in Taipei and Kaohsiung in mid-to-late March. The event will feature the world’s first AI City Pavilion, led by the ASUS Group, Foxconn, and the Taiwan Smart City Alliance. With our partners from government, civic organizations, and industry alliances, the pavilion will present the concept of sovereign AI, system architecture, and technical applications.
So what exactly is AI City? According to Peter Wu, General Manager of ASUS Cloud, it can be most intuitively understood as "An advanced form of the Smart City." While Smart Cities focus on improving convenience and efficiency for residents, AI Cities go a step further by enhancing safety, delivering more tailored services, and building greater resilience.
The concept of Smart Cities has become widely recognized over the past twenty years. Many people are accustomed to using smartphones and apps to check real-time information such as temperature, air quality, or bus arrival times. From a technological standpoint, Smart Cities are built around sensing technologies and data integration, systems that allow cities to “see” data and monitor changes, with a focus on improving efficiency and increasing transparency of information. Now, AI Cities build upon this foundation of “smartness” by enabling cities to not only see data, but also to understand it and take action.
Smart City 4.0: AI City
"AI City is essentially Smart City 4.0,” says Peter Wu. Drawing on more than a decade of experience from the ASUS Group, Wu outlines the evolution of Smart Cities in four stages. Stage one began around 2012, centered on the establishment of cloud infrastructure, where data and application became consolidated. Stage two started around 2014, when sensors began to be widely utlized in data collection from the physical environment, giving rise to the concept of Internet of Things (IoT). One of the most well-known examples from this period is the “AirBox," used to track changes in air quality. Wearable devices also gained popularity during this era, and smartwatches developed through the partnership between ASUS and Google marked an important breakthrough in digital health monitoring.
The third stage, spanning from 2017 to 2020, saw rapid advances in applications powered by AI-driven image recognition. Technologies such as smart parking systems capable of automatically recognizing license plates began to see widespread adoption. During this period, architectures began to evolve toward an edge-cloud continuum, with inference executed at the edge and training performed in the cloud.
After 2020, we entered the fourth stage. The rapid maturation of large language models, together with the technological foundations and application experience accumulated over earlier stages, has propelled us into the era of AI Cities. As AI capabilities continue to advance and the barriers to adoption decrease, future applications will become increasingly aligned with people’s needs; solving real-world problems while delivering greater convenience, safety, and resilience.
From Data Dashboards to the Foundations of Urban Governance
Data dashboards have become widely adopted across government departments thanks to years of digitalization efforts. However, the underlying data is often not fully centeralized, leaving those who need it to manually search across multiple platforms to gather critical information; an inefficient process that is also prone to error.
Take last year’s Matayen Creek overflow in Hualien as an example. Under the AI City infrastructure, event-triggered notifications could automatically alert relevant government agencies while generating accurate predictions about how the incident may unfold. The system could also identify high-priority areas and vulnerable populations, such as elderly residents living alone who may require evacuation, allowing authorities to dispatch assistance immediately.
A similar approach can also be applied to ensure that those affected by urban fires receive immediate assistance and support. When a fire breaks out in the city, multiple departments must respond simultaneously. Firefighters and medical personnel handle the emergency on-site, while the Transportation Bureau manages surrounding traffic. The Economic Development Bureau notifies nearby factories that may contain hazardous materials, and the Environmental Protection Bureau monitors potential pollution risks. Meanwhile, power, telecommunications, and water providers must closely monitor how the fire affects their infrastructure. The response continues even after the fire is extinguished, as the Social Affairs Bureau steps in to assist affected residents.
In the past, these types of cross-department operations relied heavily on phone calls and cumbersome data gathering, with officials often needing to manually search for information online before devising response measures. Under the AI City system architecture, AI can integrate data across agencies, run scenario simulations, and automate response workflows. This enables authorities to quickly identify which areas and populations may be at risk and take action immediately. By reducing reliance on the speed and vigilance of individual personnel, the system can significantly lower the risk of human error.
Sovereign AI Ensures Security and Resilience
Under the AI City framework, cities are not only beneficiaries of technological innovation but also some of the most complex producers of cross-domain data, the largest integrators of demand, and one of the most significant markets for AI applications. For this reason, cities including Manchester, Dubai, and Singapore have all chosen to leverage AI City initiatives as a means to foster new AI industry ecosystems.
While each city develops its AI City strategy differently based on varying policy priorities, industrial structure, and investment capacity, there remains a general consensus that sovereign AI is essential. Only when cities maintain control over their computing power, data, and models can they ensure security, protect privacy, strengthen urban resilience, and safeguard cultural sovereignty.
Achieving this vision requires close collaboration between government agencies, private enterprises, and independent third-party organizations. For Taiwan, this also represents a key opportunity to drive the next stage of value-added industrial transformation.
AI City: A Key Opportunity for Taiwan’s Industrial Transformation
Wu notes that since the emergence of generative AI in 2023 sparked a global surge in AI development, Taiwan has come to occupy a uniquely important and irreplaceable role in the Al supply chain. With its semiconductor manufacturing capabilities, ICT hardware supply chains, system integration expertise, hardware–software collaboration ecosystem, trusted quality, and extensive manufacturing experience, Taiwan has become one of the few economies to tangibly benefit from the global AI boom, seeing both economic growth and stock market valuations ranked among the strongest worldwide.
Leveraging Existing Strengths for Rapid Iteration and Innovation
Following its global dominance in the AI hardware market, Taiwan’s next crutial step is how to leverage its strengths in AI and ICT hardware manufacturing. By using cities as real-world application environments, Taiwan aims to bring together hardware and software partners under a sovereign AI framework to develop a comprehensive AI ecosystem that drives both urban and industrial transformation.
Due to the island's industrial structure, many software companies in Taiwan operate at smaller scales, focusing on project-based services, and lacking products with strong market influence. It is interesting to note, however, that this type of business model actually provides deep insight and knowledge into customer needs and industry challenges. In many cases, the service providers understand operational problems better than their clients and are able to adapt solutions quickly through flexible customization. In the era of AI, these capabilities have become an irreplaceable core advantage of Taiwan’s software service industry.
Wu emphasizes that as AI City development becomes a clear priority for many countries, Taiwan’s complete technology supply chain and real-world implementation experience are seen as strong advantages. Recognizing this opportunity, ASUS, the Foxconn Group, and multiple technology companies have jointly formed an AI City national team, which was officially introduced at this year’s Smart City Expo. This initiative aims to ride the wave of AI and create increased value through hardware and software industry collaboration. Cities such as Tainan, Yunlin, and New Taipei will serve as implementation sites, where government resources and the technology industry come together to drive broader industrial development.
"Many countries and cities are paying close attention to Taiwan’s next step in AI development." says Wu. Numerous governments and enterprises abroad are seeking an all-encompassing solution spanning semiconductors, AI computing power, platforms, and applications to accelerate their AI transformation. At a time when the traditional model of globalization is shifting and geopolitical risks are rising, an AI City architecture built on sovereign AI offers a compelling path forward. With its complete ICT supply chain, strong system integration capabilities, and practical experience deploying sovereign AI within a democratic governance environment, Taiwan stands out as one of the most trusted partners for countries seeking to build their own AI ecosystems.
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Autor(en)/Author(s): Betty Yang
Dieser Artikel ist neu veröffentlicht von / This article is republished from: AI City, 01.03.2026
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