Insights

 

Asia is rising as a global innovation leader. Across the region, innovation has emerged as a strategic lever, driving economic growth while accelerating the transition to net zero. It is estimated that advancements in sectors such as clean energy, smart buildings, and sustainable transport could generate trillions in new revenue opportunities by 2030.

Achieving Asia’s net zero goals does not depend solely on entirely new scientific breakthroughs. It calls for harnessing established technologies, while advancing innovation to commercialise untested solutions, and scaling their deployment across the region.

An estimated 35% of global emission reductions required by 2050 will need to come from technologies still in development. Continued innovation will be crucial to bring these technologies to market and make them commercially viable for widespread adoption.

We spoke with two of our ASIA Panel members who have witnessed these shifts firsthand – Dr. Andrew Benedek from Anaergia Inc, who pioneers innovative circular infrastructure systems in water and waste management, and Satish Shankar from Bain & Company, who helps organisations navigate digital transformation to reshape how infrastructure is built, managed, and operated.

 

Q: Let's start with the big picture. How is technology transforming the way we approach infrastructure development?

Satish: Global cities and industries are using AI-driven systems to optimise resource use, reduce emissions, and improve quality of life. In Asia – home to fast-growing cities and massive infrastructure needs – AI-driven technologies are creating new opportunities to enhance efficiency, sustainability, and value across various asset classes.

For example, Bain & Company recently supported a leading energy company whose field engineers deliver electrical services for buildings. We helped them pilot a Generative AI-powered knowledge management tool that automates routine, time-consuming tasks like handling customer queries.

With the tool, combined with upfront investment in training, field engineers saved approximately 20% of their time, redirecting it towards their core responsibilities: designing, maintaining, and managing construction projects for power delivery.

However, several barriers remain to unlock AI’s full potential in the infrastructure sector, including skills gaps, cultural resistance to change, difficulty in attracting top talent, and uncertainty around return on investment. Addressing these challenges hinges on a few key success factors:

• Think big: Set bold ambitions aligned with industry trends and supported by clear success metrics. Assess organisational readiness to define the starting point.
  
  
• Start small: Focus on realising value immediately. Develop a roadmap of AI use cases where technology can solve specific problems, then scale up successes continuously.
  
  
• Scale fast: This requires continuous orchestration and change management (e.g., recruiting, upskilling, and retaining relevant talent) while aligning skills with performance management. Design data, processes, and technology to be easily accessible to support new ways of working.
  
  

Dr. Benedek: In water infrastructure, we're seeing technology address the challenge of demand (for water resources) consistently exceeding availability. Membrane technology has been instrumental in recycling water and creating new sources through seawater desalination.

I believe all water systems should be built with recycling capabilities, and wherever there's sea access, desalination should be part of the solution mix. Like computer chips, membrane technology enables the construction and operation of smaller, distributed systems.

In a typical city, 80% of urban water infrastructure costs go towards building pipelines that convey water to and from large central treatment plants. Today, we can achieve significant savings by building distributed, automated systems across the various valleys or regions of a metropolitan network.

 

Q: What emerging technologies are you seeing that could really scale this kind of transformation across different infrastructure sectors?

Satish: [Compared to other sectors,] AI adoption is still nascent in the infrastructure space, but the potential for value is enormous. There are already emerging examples of its impact in our region, such as:

• Predictive Maintenance: Machine learning algorithms analyse sensor data and past failure patterns to predict when infrastructure components need repair or replacement. In China, authorities are installing real-time sensors on highways and railroads to continuously monitor structural health and enable preventive maintenance, rather than reactive repairs. This lowers the risk of catastrophic failures, enhances safety, and can significantly reduce maintenance costs through timely intervention.
  
  
• Digital Twins and Simulation: Infrastructure managers are embracing digital twin models (virtual replicas of physical assets) to run simulations and optimise performance. Advanced twins enable maintenance prioritisation and reliability simulations at network scale. At Nanyang Technological University (NTU) in Singapore, deploying a digital twin identified optimisation opportunities that reduced building energy consumption by 31% and carbon emissions by 9.6 kilotons.
  
  
• Internet of Things (IoT) Sensor Networks: Low-cost sensors and IoT devices provide real-time infrastructure data. Embedded instrumentation in roads, pipelines, power lines,  and buildings continuously relays data on strain, vibration, temperature, and other parameters that AI models analyse to detect anomalies. In Australia, AI-driven analytics combined with sensor inputs enable Melbourne Water to predict recycled water quality two days in advance with 75% accuracy.
  
  
• AI-enabled Design: In a 2024 global survey of senior infrastructure leaders, the design phase was identified as where AI offers the most significant potential value. Generative design mitigates design error risk by producing multiple iterations based on wide-ranging constraints. It reduces manual, non-creative efforts, and enables rapid option evaluation, which is particularly valuable for large-scale infrastructure projects. As design considerations multiply, from energy performance to material costs to sustainability regulations, AI-powered tools enable rigorous design at speed.
  
  
• Robotics and Automation: Combining AI software with robotic hardware unlocks unprecedented automation opportunities. Construction robotics improves adaptability and operational speed by analysing big data to predict issues and optimise task sequences. Drones are increasingly used for inspections and maintenance tasks that are dangerous or tedious for humans. Coupled with AI analytics, these technologies ensure maintenance crews focus on the most critical issues.

 

Q: How can technology improve infrastructure planning and design to better address sustainability challenges?

Dr. Benedek: Waste management exemplifies both the challenge and opportunity. We've developed effective technologies for recycling metals and some plastics, but most lower-grade plastics, paper, and food waste still end up in landfills worldwide. I believe all three waste constituents can be recycled when economics are favourable.

As with water systems, a significant portion of overall waste handling costs comes from collection. In developed countries, recycling often mandates separate pickup for each waste type to facilitate processing. I believe there is room for improvement in this approach as it burdens households with separation requirements, and creates extra costs and traffic congestion from multiple waste trucks.

A better solution is developing robust technologies that can recycle these components from mixed waste at modern waste recovery facilities. This technology exists today and represents a more efficient, scalable approach to waste management.

Satish: On one hand, AI has tremendous potential to reduce emissions – in Southeast Asia alone, it could cut carbon emissions across agriculture, power, and transport systems by 3-5% annually.

At the same time, the widespread adoption of AI is driving a surge in demand for underlying digital infrastructure such as data centres, fibre networks, and cloud computing capacity, significantly increasing energy consumption. Training and operating large AI models require substantial computing power, often powered by energy-intensive data centres.

The International Energy Agency projects that data centre electricity use will more than double by 2030, surpassing Japan's current total electricity consumption. This creates real infrastructure challenges. Electricity grids are already strained in many places, and around 20% of planned data centre projects could face delays if we don't address these energy demands.

We face a dual imperative: use AI to make existing infrastructure smarter and more efficient, while simultaneously preparing our energy systems to handle AI's growing demands. This requires innovation in grid modernisation, renewable energy integration, and more efficient cooling and power systems for data centres.

The reality is there's no AI without the enabling infrastructure, but AI also has the potential to transform how we build and operate that very infrastructure. It is a complex feedback loop, but one with enormous potential if we get it right.

 

Q: What role do you see ASIA Panel playing, and how do you hope to contribute to accelerating sustainable infrastructure development across Asia?

Satish: Through our diverse expertise, the ASIA Panel members can offer practical guidance on financing models (such as blended finance and public-private partnerships), emerging technologies, and implementation pathways. Collectively, this will enable us to develop actionable roadmaps that facilitate a just, swift, and scalable transition.

In addition, Singapore is a hub for sustainable infrastructure, with significant innovation emerging that is transferrable to the wider region. The ASIA Panel creates an opportunity to share best practices across the region.

Together with my fellow Panel members, I look forward to help lay the groundwork for a more resilient, inclusive, and climate-aligned infrastructure future across Asia.

 

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What drives Dr. Benedek and Satish’s approach to sustainable infrastructure:

Dr. Benedek's approach is driven by his deep concern over increased resource consumption driven by our rapidly growing population. He focuses on waste-to-resource technologies that work in harmony with nature, believing innovation must keep pace with population growth to avoid irreversible ecological damage.

He was also awarded the Lee Kuan Yew Water Prize 2008 for his outstanding work in pioneering the development of low-pressure membranes in water treatment.

Satish's approach is driven by contrasting experiences between developing and developed markets, from infrastructure constraints to sophisticated systems that enable economic dynamism. He views sustainability as both a moral imperative and generational opportunity, recognising that infrastructure adaptation has moved from a peripheral concern to core strategic advantage.