Digital transformation and data-driven decision-making lead as priority areas, followed by climate resilience and improvements in project delivery, in a survey of more than 100 senior infrastructure leaders across Asia Pacific

These priorities reflect mounting pressure on infrastructure systems, including rising energy demand, capacity constraints and tighter interdependencies that influence what can be delivered in practice, said  the Asia Pacific Infrastructure Innovation Index 2026, a new thought leadership report launched by AECOM, a global infrastructure leader, and the Urban Land Institute (ULI).

Innovation now centres on strengthening how infrastructure is planned, delivered and operated. The emphasis is on continuity, efficiency and risk management rather than pursuing standalone technological advancement, it said.

The report brings together perspectives from stakeholders across infrastructure, government, utilities, investment, planning and development sectors. It draws on a survey of more than 100 senior infrastructure professionals in Asia Pacific, alongside in-depth interviews with industry leaders. As the first edition of the Index, it establishes a baseline for understanding how infrastructure innovation is currently being prioritized and delivered across the region.

"This report highlights how organisations are moving beyond ideas and applying innovation in practical ways to improve delivery, resilience and system performance," said Ian Chung, chief executive of AECOM's Asia region. "Infrastructure leaders across Asia Pacific are responding to growing complexity by strengthening digital capabilities, improving coordination across interconnected systems and focusing on long-term operational performance."

"Our collaboration with AECOM reflects a growing recognition that infrastructure and real estate are increasingly interdependent," said Alan Beebe, CEO Asia Pacific, ULI. "As cities in Asia Pacific evolve, infrastructure is no longer just a technical consideration, but plays a critical role in shaping how places function, grow and perform. Understanding how innovation is being applied in this context is essential for those involved in the built environment."

The 10 key takeaways from this study are as follows:

* Innovation is shifting towards coordination and integration, rather than new technology. Most of the required technologies already exist, but they must be integrated across systems by addressing challenges around financing, governance, risk management, data integration and skills development.

* Climate resilience is focused on operational reality. Extreme weather across the Asia Pacific region means economic continuity and operational preparedness are prioritized above future climate eventualities, requiring investment in response capability, system coordination and recovery planning — not just higher design thresholds.

* Energy and resilience constrain infrastructure delivery and performance. Power availability, system stability and recovery capability impact what can be built, financed and operated. Beyond adding generation, this also needs to address grid readiness, system integration and demand management.

* Local context and capabilities matter. Proven global approaches and innovations work best when tailored to local capacity and economic development, e.g. more targeted, operational approaches to flood resilience in developing markets instead of complex, fully-integrated solutions.

* The value of AI lies in augmentation, not automation. The real value of AI is in supporting professional judgement, improving speed and consistency in complex environments. In turn, AI needs to be supported by strong data and data management.

* More innovation in financing is required. Affordability constraints, limited planning capacity and underdeveloped public-private partnership models restrict the flow of private capital into infrastructure, highlighting the need for more sophisticated financing approaches, including the recognition of social value in investment decisions.

* The industry needs system-level efficiency and integrated planning. Most current approaches focus on the asset level but a district- or system-level approach should produce better results.

* Existing infrastructure represents the greatest climate vulnerability. Assets such as tunnels, bridges and underground systems cannot be easily modified once built, shifting the focus toward protecting surrounding systems and managing residual risk.

* Over-reliance on AI risks eroding professional judgement. Excessive dependence on AI-generated outputs — particularly for long-term forecasting — may weaken human expertise and lead to underestimation of systemic risks which current models cannot capture.

* Data centres emerge as a systemic pressure point. Ironically, the digital infrastructure which enables AI augmentation is straining electricity generation and grids. This requires data centers to be planned and delivered in tandem with energy systems.