Digital twins and artificial intelligence are becoming the intelligent operating layer for cities, moving beyond isolated pilots and dashboard demonstrations to the core of urban management. In a 2026 virtual summit panel discussion, experts explored how local governments can use these tools to shift from reactive crisis management to a more strategic, risk-based approach to infrastructure resilience. The conversation also examined how energy systems can be shaped by local authorities through renewable generation, demand-side flexibility, storage, and smarter networks.
A strategic, risk-based approach to infrastructure resilience
One of the central themes was the need for a strategic, risk-based approach to infrastructure resilience. Traditional infrastructure management tends to be reactive, with investment decisions made after failures or after risk assessments that rely on static data. Digital twins provide a dynamic, continuously updated replica of physical assets, allowing city planners and operators to simulate different stress scenarios, such as flooding or heat waves, and observe how interdependent systems respond. AI adds a further layer of intelligence by detecting patterns, predicting failures, and recommending pre-emptive action. Instead of spreading limited budgets across every possible risk, cities can prioritize interventions based on consequence, vulnerability, and cost-effectiveness.
Shaping energy systems with renewables, flexibility and storage
Another key discussion point centered on how local authorities can shape energy systems through renewables, flexibility, storage and smarter networks. The shift to decentralized energy creates both opportunities and challenges. Cities can use digital twins to model local generation, grid constraints and storage capacity. AI can optimize the operation of flexible assets such as batteries, electric vehicle chargers and heat pumps, helping balance supply and demand in real time. Local authorities have a unique role to play through planning powers, procurement, and partnerships with network operators and community energy groups. By integrating these functions into a broader city operating layer, they can reduce carbon emissions, lower fuel poverty, and increase energy security.
Moving AI from pilots to real-world impact
The panel also built on a broader industry conversation about AI moving from pilots to real-world impact. During an in-depth conversation with Professor Jung Hoon Lee, a leading academic voice on smart cities, the discussion turned to the latest global smart city index and the emergence of what he calls the “AI super gap” between cities. This gap, he suggested, may be even more consequential than previous digital divides. Cities that invest early in data platforms, AI-ready infrastructure and effective governance are likely to pull ahead in service delivery, economic productivity and sustainability; those that do not risk falling further behind. The professor argued that the next phase of urban innovation will be determined less by individual algorithms or flashy proofs of concept and more by the quality of municipal data, robust computing capacity, and the institutional ability to govern AI responsibly.
Expanding a private city: Cayala’s agile transformation
A concrete example of these principles in action comes from Cayala, one of Central America’s largest private cities. Juan Carlos Lopez, CTO and Chief of the Value Management Office at Cayala, explained how agile transformation, digital infrastructure and community-led services are supporting the city’s expansion. In a private city model, delivering services efficiently is vital because there is often a closer link between residents, businesses and the operator. Lopez noted that digital infrastructure is not just about connectivity or sensors; it is about creating an agile management culture that can respond quickly to changing needs. Community-led services, meanwhile, ensure that residents are not passive recipients of technology but participants in planning and operating their environment. Cayala’s experience shows that a strong digital foundation, combined with an iterative and flexible approach, can turn a large urban development into a smart place to live and work.
Sunderland’s measurable smart city benefits
The city of Sunderland provides further evidence that smart city programmes can deliver measurable benefits. A smart city programme has produced quantifiable economic, social and public-service benefits, according to new research. The findings highlighted the importance of long-term connectivity investment, civic leadership and trusted partnerships in transforming digital ambition into real impact. Sunderland has also positioned itself as a leading smart city by using digital infrastructure and low-carbon innovation to build a resilient, future-focused economy. The city’s experience confirms that lasting change requires more than technology procurement; it demands consistent leadership, a shared vision and collaboration across the public, private and educational sectors. An on-demand webinar on preparing for AI further explored Sunderland’s work on data groundwork, emphasizing that data governance and interoperability are essential before advanced analytics and machine learning can be deployed effectively.
Singapore’s continuing smart nation journey
On a national level, Singapore continues to strengthen its reputation as one of the world’s smartest nations. A city profile of the island city-state documented how Singapore is integrating digital twins, sensors, and AI into urban planning, transport, housing and government services. Singapore has long pursued a whole-of-nation strategy that combines high-level strategic direction with practical deployment at district and building scales. Its virtual Singapore digital twin has become a reference for other cities, enabling testing of planning scenarios, wind flow, accessibility and resource use. The Singapore example illustrates the importance of a centrally coordinated data platform, sustained public investment, and a governance framework that allows experimentation without compromising privacy or security.
AI in transport: data foundations and responsible governance
The role of AI in transport also received attention. As transport agencies turn to AI to improve services, the greatest opportunities depend on strong data foundations, workforce readiness and responsible governance, according to Katherine Flesh, a technology executive participating in the discussion. AI can help optimize traffic signals, predict maintenance needs, plan transit routes, and personalize passenger information. Yet the quality of these applications is only as good as the data feeds them. Many agencies still struggle with fragmented datasets, legacy systems, and limited data-science capacity. Flesh emphasized that agencies should invest in data pipelines and staff skills before implementing large-scale AI. Responsible governance, including clear accountability and transparent algorithms, will be key to building public confidence.
AI for personalised government services and trust
The use of AI for personalised government services is another area with significant potential to improve trust and inclusivity in cities. Personalisation can mean tailoring public information, social services and administrative processes to the circumstances and preferences of every resident. But if it is not designed carefully, it can also reproduce bias, exclude vulnerable groups, or feel intrusive. A panel discussion on this topic highlighted the need to co-design AI services with users, especially those who are most likely to be marginalized. Building trust requires clarity about what data is collected, who can access it, how decisions are made, and what remedies are available when something goes wrong. Inclusivity should be built into service design from the start, not added as an afterthought.
Priorities for healthier, more sustainable cities
Source:Smart Cities World News