Agentic AI set to boost global infrastructure productivity: new EY report

• Despite strong investment, global infrastructure faces a US$64t funding gap globally; close to US$140t investment required between now and 2050 to address this shortfall
• Project rework and abortive work can add as much as 15% to overall costs, contributing to hundreds of billions in lost value
• Agentic AI creates an intelligence layer, integrating data from siloed systems reducing the need for holistic reconfiguration of the construction value chain and enabling faster, more informed decisions

Despite investment in in recent years, the global infrastructure sector faces a significant funding gap of US$64t globally.¹ World governments and the private sector will need to invest close to US$140t between now and 2050 to address this shortfall, keep up with ever-shifting global conditions and provide for the needs of the world's population. A considerable uplift in productivity is required.

Infrastructure productivity is constrained not by a lack of technology, but by fragmented systems, data and stakeholders that limit effective coordination.

The report, The intelligence layer: how agentic AI can connect the infrastructure industry, explores how governments and organizations can embed agentic AI project, program and portfolio structures to improve coordination between segmented, yet highly interdependent, data sources. While current delivery models require manual coordination and periodic reporting, agentic AI introduces a continuous model that examines data in real time, seamlessly routing it across systems. While agents surface and connect insights at scale, humans apply domain expertise, exercise judgement and remain accountable.

According to the report, investment in digital tools to improve efficiency and streamline workflows has not compounded across projects, programs or portfolios as productivity gains have remained localized. Data is disconnected across silos, limiting visibility and inhibiting coordination.

Industry standards show that rework alone can account for up to 15% of total project costs, with hundreds of billions in lost value. Agentic AI, when considered in the context of an intelligence layer, addresses these issues by acting as a connective layer, sitting above and between existing systems, delivering clear, actionable insights in real time, thereby enabling infrastructure professionals to shift focus away from time-consuming administrative tasks. This shift expands decision-making complexity and deliver critical infrastructure at scale with the same workforce.

Steve Lewis, EY Global Infrastructure Technology Leader, says,

"The intelligence layer provided by agentic AI goes far beyond automation. It enables deep analysis, interpretation and decision-making by removing barriers to historically siloed datasets and converts fragmented information into actionable insights. Agentic AI frees talented professionals from administrative burdens, giving greater latitude to focus on governance, negotiation and relationship-building, and ultimately allowing people to focus on the work they are best placed to do."

A governance framework based on five critical areas is required

For agentic AI to thrive, agents must be able to reason across organizational boundaries and across multiple information sources that were originally designed to remain separate. This places an onus on having the right enabling governance in place. The report provides a governance framework based on five critical areas: accountability and legal liabilities; transparency and explainability; data sovereignty and commercial confidentiality; human oversight and competence; and systemic resilience.

Lewis says, "As these capabilities scale, establishing clear governance, accountability and data foundations will be critical to supporting consistent and effective decision-making. The next question is how governments and organizations will adapt to this structure at the pace needed."

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Notes to editors

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