Urban infrastructure has long been managed through maintenance schedules, emergency response, and institutional memory. Today, a growing number of cities are exploring how digital twins and artificial intelligence can turn this fragmented approach into a more strategic, risk-based system. By combining real-time data, predictive analytics, and scenario planning, local governments can anticipate failures, optimise energy use, and design services that respond to residents' actual needs. A 2026 virtual summit panel discussed how these technologies are reshaping the way cities manage everything from power grids and streetlights to transport networks and buildings.

Key facts at a glance

• Digital twins and AI are helping cities shift from reactive maintenance to risk-based infrastructure management.
• Local authorities can shape energy systems through renewables, flexibility, storage, and smarter networks.
• Glasgow City Council Leader Susan Aitken has credited leadership, courage, and community engagement for the city's climate action progress over nine years.
• Susan Aitken is stepping down after leading the council for nine years.
• Professor Lily Kong, President of Singapore Management University, argues cities should move beyond resilience toward regenerative and restorative urban systems.
• Sunderland is using digital infrastructure and low-carbon innovation to build a resilient, future-focused economy.
• Dublin is applying digital twin projects, traffic reduction measures, and economic growth strategies to improve community services.
• Smart lighting networks must be secure, interoperable, and future-proof as cities adopt them.
• Microsoft's Katherine Flesh says AI in transport depends on strong data foundations, workforce readiness, and responsible governance.
• Ecomondo highlights practical solutions and partnership-building for healthier, more sustainable cities.

From reactive repairs to strategic risk management

Many local authorities still allocate budgets based on historical patterns rather than current condition. That is beginning to change. A digital twin allows cities to maintain a living replica of physical assets, updated with sensor data and operational records. AI can then process the information to identify patterns, predict deterioration, and recommend interventions before a failure occurs. For city managers, this changes the question from “what has already broken?” to “what is most likely to break next, and what are the consequences?” Risk-based approaches allow limited budgets to be directed toward the assets and communities that face the greatest threats, from flooding to equipment failure to energy poverty.

The panel emphasized that digital twins and AI are not simply about efficiency. They are also about equity. When data is broken down by neighbourhood, it reveals differences in infrastructure quality, response times, and exposure to environmental risk. Cities can use that information to prioritise investments where they are needed most, rather than where the loudest voices demand attention. This requires robust data governance, clear ownership, and the ability to translate analytical insights into political decisions.

Local authority leadership in energy systems

Energy is one of the most promising areas for this approach. The panel highlighted that local authorities have a major role in shaping energy systems. Cities can use their planning powers, purchasing decisions, and public assets to accelerate the transition to renewables. They can also support flexibility services, which reward consumers and businesses for shifting electricity demand to match supply, and invest in storage to balance intermittent sources such as wind and solar. Smarter networks—using sensors and digital control to manage voltage, reroute power, and integrate electric vehicles—are essential if urban areas are to meet net-zero targets.

Digital twins of energy grids can help authorities model the impact of new electric vehicle charging points, heat pumps, and rooftop solar systems before they are built. Instead of installing equipment and hoping the network can cope, planners can simulate different scenarios, identify bottlenecks, and design interventions that make the whole system more resilient. Local authorities can also use AI to optimise the operation of municipal buildings, public lighting, and fleets, reducing both costs and emissions.

Glasgow's climate journey

Real-world leadership is crucial. Susan Aitken, Leader of Glasgow City Council, used her time in office to position the city as a global superpower of local climate action. As she prepared to step down after nine years at the helm, Aitken reflected on the combination of leadership, courage, and community that drove the transformation. Under her tenure, Glasgow created a climate action plan designed to cut emissions at the speed and scale necessary for a fair transition. The city has faced difficult choices, including retrofitting housing, expanding active travel networks, and engaging communities that had historically been excluded from environmental debates.

Aitken's departure is a reminder that institutional change must outlast individual politicians. The capacity to sustain climate progress depends on embedding data systems and citizen engagement into everyday council decision-making. People need to see that their own lives are improved by digital infrastructure, not just that the city is becoming a showcase for technology.

From resilience to regeneration

Professor Lily Kong, President of Singapore Management University, offered a broader vision. She argued that cities must move beyond resilience to become regenerative, restorative, and sensitive to community needs. Resilience, in her view, is often about bouncing back to the same state after a shock. But cities today need to bounce forward—improving social equity, ecological function, and economic opportunity. Regenerative cities go further by restoring the natural systems that support urban life: water cycles, biodiversity, clean air, and healthy soils.

Technology can support this agenda by making visible the hidden relationships between infrastructure and nature. A digital twin, for example, can show how a new development might affect local flood risk, shade, or wildlife corridors. But Kong's emphasis on sensitivity reminds us that data alone cannot answer ethical questions about who benefits, who loses, and who gets to participate. Her message is particularly important as artificial intelligence is increasingly used to automate decisions about urban services.

Sunderland and Dublin: two digital city strategies

Two city examples illustrate the practical potential of these ideas. Sunderland has been repositioning itself as a leading smart city by combining digital infrastructure with low-carbon innovation. The city sees these investments as a way to build a resilient, future-focused economy and attract jobs in advanced manufacturing, software, and clean energy. Its strategy includes creating a high-quality fiber network, developing a digital twin to support planning, and working with partners to pilot new mobility and energy services. The goal is not simply to install sensors but to change the way the local government operates and collaborates.

Dublin has pursued a similar agenda with a different emphasis. The city is innovating to improve experiences and services for its communities through digital twin projects, traffic reduction, and economic growth initiatives. Dublin has explored how digital twins can be used for urban planning, allowing officials to test the impact of new buildings, cycling routes, and bus corridors in a virtual environment. Traffic reduction measures aim to reduce congestion and improve air quality while making the city more attractive for walking, cycling, and public transport. These changes are designed to support economic growth by making Dublin a more liveable place for workers and businesses.

Smart lighting and cybersecurity on the streets

Another session in the summit focused on smart lighting. Cities are discovering that streetlight networks can serve as a backbone for a wide range of internet-of-things applications, from air quality monitoring to occupancy detection. But the conversion to LED and networked lighting also introduces new cybersecurity risks. A city with tens of thousands of connected lights is an attractive target for malicious actors seeking to disrupt services or gain access to municipal networks.

The discussion highlighted the need for carefully procured hardware, regular security testing, and standards that support interoperability between different systems. Cities should treat lighting infrastructure as part of the broader digital ecosystem, not as a set of isolated devices. The second episode of a related series examined the technology and considerations behind making streetlight networks secure, interoperable, and future-proof. This is a matter of both public safety and operational efficiency. Poorly secured lighting networks could be used to launch cyber attacks on other city systems, so procurement and management need to be treated with the same seriousness as core IT systems.

The data and governance behind AI transport

Transport is another area where AI and data are transforming operations. Katherine Flesh of Microsoft observed that the greatest opportunities will depend on strong data foundations, workforce readiness, and responsible governance. She said that transport agencies are eager to use AI to improve services, but the quality of their models depends on the quality of the data they feed into them. Many cities are still facing gaps in data collection, interoperability, and governance. Without clean, well-structured data from sensors, vehicles, and payment systems, AI algorithms will produce unreliable forecasts and recommendations.

Workforce readiness is equally important. Machine learning adoption must build confidence and willingness to act, without requiring everyone to become a data scientist. Transport planners need to understand what AI can and cannot do, how to validate results, and how to raise concerns. Responsible governance is also critical. Citizens expect transparency about how their data is collected, used, and protected. If transport agencies deploy AI in ways that feel intrusive or unfair, they risk losing public trust. AI can reduce delays, improve traffic signal timing, and identify maintenance needs, but the technology must be used ethically and accountably.

Sharing practical solutions

Finally, the need to share practical solutions was underscored by Ecomondo, the Italian platform for green technologies and innovation. Ecomondo discussed the priorities shaping healthier, more sustainable cities and explained why a global summit offers a valuable platform for exchanging ideas and building new connections. The organisation argues that technological innovation is essential, but it must be connected with policy, finance, and community participation.

Across all of the sessions, a consistent theme emerged: digital twins and AI are powerful tools, but they are not silver bullets. They work best when combined with clear leadership, strong data governance, and genuine community engagement. Cities that succeed in reshaping infrastructure management will be those that treat technology as a means to improve the lives of residents, not as an end in itself.

Source: Smart Cities World News