Smart City Summit & Expo 2026: Advancing the AI City Vision with ASUS

The Smart City Summit & Expo / Net-Zero City Expo 2026 showcased practical AI applications in urban environments, demonstrating the shift from concept to real-world implementation. At the AI City Pavilion, a world’s first, ASUS presented its “AI City” vision, introducing an integrated five-layer architecture that connects infrastructure, platforms, and applications into a deployable ecosystem for cities.

Through the exhibition and the AI City International Forum, ASUS convened global stakeholders from industry, government, and academia – driving the exchange of perspectives and exploration of pathways from pilot projects to city-wide deployment.

To deepen these discussions, ASUS executives elaborated on the practical implementation of AI City concepts. They shared insights on governance models, sustainability strategies, and sovereign AI models, and how these elements support scalable urban transformation.

ASUS Hosts AI CITY International Forum in Taiwan

Shaping the Next Phase of AI-Driven Cities

Building on the forum’s discussions, several key themes emerged, underscoring how ASUS is helping to define the next phase of urban innovation. Samson Hu, ASUS Co-CEO and Chairman of Taiwan Smart City Solutions Alliance (TSSA), emphasized the evolution toward AI City represents more than a technological shift—it signals a transformation in how cities operate, make decisions, and scale intelligence across systems. AI is truly empowering smart cities to make a meaningful impact on the daily lives of their citizens. Furthermore, the shift to predictive governance, sovereign AI, and scalable deployment models signals a broader move toward more resilient, autonomous, and globally adaptable urban frameworks.

AI is turning smart city models into more intelligent, autonomous systems. This shift is enabled by advances in AI and by the holistic integration of these technologies across infrastructure, platforms, and applications. At the same time, ecosystem collaboration—especially leveraging Taiwan’s ICT and semiconductor strengths—strengthens ASUS’s ability to deliver complete, deployable AI City solutions globally.

Key takeaways include:

• Strategic planning with AI: AI enables cities to stop just reacting and start planning ahead, making better decisions across transit, health, energy, and safety.
• City-run AI as the brain: When cities control their own data, computers, and AI, they stay safer, keep their rules, and can manage things in their own way.
• From components to full AI City systems: With support from Taiwan, ASUS develops modular, scalable systems that enable cities to adopt AI incrementally while ensuring security and adaptability for diverse global needs.

Sovereign AI for Cities: A Reference Stack from Compute to Curbside

During his speech at the Summit, Peter Wu, CEO of ASUS Cloud and Taiwan AI Cloud, highlighted sovereign AI as a foundational enabler for AI-driven cities. He emphasized that as cities increasingly rely on AI for critical operations, maintaining control over data, infrastructure, and models is essential to ensuring security, autonomy, and long-term scalability. Sovereign AI is not only a technological approach but also a strategic framework that allows cities to innovate while preserving governance over their digital assets.

As a pathway to achieving this, Peter introduced a five-layer architecture for AI City development that helps cities move systematically from basic infrastructure to real-world applications. The framework includes sovereign computing, local model development, platform integration, application deployment, and innovation ecosystems. Together, these layers provide cities with a blueprint from proof-of-concept to operational AI environments.

Localizing computing and AI models was also emphasized, as keeping data within jurisdictional boundaries enables advanced AI while meeting local requirements. For example, Taiwan AI Cloud demonstrates how supercomputing, local-language models, and integrated platforms help cities build secure, hybrid AI environments that support transportation, public safety, energy management, and citizen services.

Key takeaways for city sovereign AI include:

• A layered architecture for scalable AI Cities: The five-layer framework—spanning sovereign compute, sovereign models, platforms, applications, and innovation—provides a structured pathway for cities to evolve from pilot projects to large-scale deployments.
• Local-first approach to computing and models: Deploying localized infrastructure and regionally trained models enables cities to meet data governance requirements while still leveraging advanced AI capabilities.
• End-to-end integration from infrastructure to applications: A unified ecosystem that connects supercomputing resources, AI platforms, and real-world applications allows cities to operationalize AI across domains efficiently.
• Ecosystem-driven innovation: Collaboration between government, industry, and AI partners plays a critical role in accelerating AI adoption, fostering new use cases, and enabling cities to continuously evolve their digital capabilities.

ASUS Group Initiates AI City with Whole City Export Model Mapping Out a New Smart City Blueprint

From Smart to Sustainable: How Cities Turn Intelligence into Impact

Also during the Summit, Albert Chang, Corporate Vice President and Co-General Manager of the ASUS AIoT Solution Business Group, explained how cities can turn intelligence into measurable sustainability. As urbanization accelerates, cities face climate and resource challenges. Digital infrastructure must go beyond convenience to directly support net-zero goals.

Cities operate across layered digital systems, but fragmentation among sensors, platforms, and dashboards persists. Without integration, data is disconnected, insights are delayed, and risks may only be found after failures occur. A unified data foundation is needed to provide real-time visibility, actionable intelligence, and predictive decisions.

For ASUS, sustainability is not an add-on, but a core principle of intelligent systems from the start. Integrating data from transportation, energy, water, and buildings helps cities shift from reactive to proactive governance, improving efficiency and resilience.

Key takeaways:

• From Data Silos to Shared Intelligence: Sharing data across city technology helps turn raw numbers into useful facts, making it easier for city workers to see what’s happening, work together, and make better choices.
• From Reactive Operations to Predictive Management: With AI and data, cities can go from simply looking back at problems to predicting what might happen, enabling them to prevent issues and better manage resources and city activities.
• Turning Data and AI into Measurable Impact: Using both data and AI together means cities get a steady stream of facts that lead to smart actions, enabling them to save energy, cut pollution, and keep people safer.
• Proven AI Use Cases Across Global Cities: Real AI deployments in places like Europe, Japan, and Taiwan—such as safety cameras and tech to keep buses on time—demonstrate that cities can address urban challenges with the right implementation.

Vice-President Bi-khim Hsiao and the AI City Partnership at the launch ceremony

The Road Forward for AI Cities

Moving forward, progress will depend on how effectively different stakeholders align. Governments, industry partners, and technology providers each contribute to the design of infrastructure, the establishment of standards, and the deployment of solutions at scale. ASUS’s approach reflects this reality, combining technological capabilities with ecosystem partnerships to support implementations that can grow beyond individual projects and evolve into citywide systems over time.

As these efforts continue to evolve, the emphasis will remain on solutions that are practical, scalable, and adaptable—supporting cities that are more connected, more resilient, and better prepared for what lies ahead.

Explore more about AI cities and ASUS initiatives here: AI City: The Next Stage in the Evolution of Smart Cities