The acceleration comes as companies prepare for tougher climate-related disclosure rules under Singapore Exchange regulations and navigate guidance on greener digital infrastructure. Yet, only 35% of Singapore organisations use AI centrally to drive environmental decisions, creating a gap between ambition and execution.
The disconnect is particularly stark, given that 52% of organisations cite unclear return on investment and difficulty measuring impact as key barriers to progress – the very challenge AI deployment could address.
"Rising disclosure requirements and increasing pressure for real-time reporting are driving the need for AI, automation, and trusted data platforms. When sustainability is built into core business operations, businesses can gain clearer insights that help them make smarter, data-driven decisions,” says Guat Ling Ang, managing director at Kyndryl Singapore.
Stronger integration but uneven tech foundations
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Singapore shows one of the highest concentrations of integration-focused organisations globally at 35%, compared with the 16% global average. Some 52% have embedded sustainability as a core driver of innovation and cost savings, versus just 17% worldwide.
Technology teams are increasingly taking the lead, with 58% of Singapore organisations saying their IT departments now drive sustainability goals across the enterprise, up from 40% in 2024. Nearly two-thirds (63%) report strong alignment between IT and sustainability teams.
Predictive AI adoption is rising. More than half (63%) of organisations forecast resource use and emissions to anticipate future impact, while 53% focus on anticipating climate risks.
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"More than half of leading organisations now use predictive AI to anticipate and act on sustainability challenges—rather than just to track and analyse—making forward-looking intelligence central to sustainability strategy," says Ricardo Davila, general manager of enterprise partner solutions at Microsoft.
Still, data infrastructure remains a structural hurdle. Half of organisations struggle to collect data from internal systems, while 43% contend with missing or incomplete information, blocking reliable AI insights.
The bottleneck is steering companies to continue prioritising quick wins. They are focusing on energy-efficient hardware and systems (80%), server utilisation and consolidation (67%), and financial operations (63%). Lifecycle actions lag, with only 33% extending asset life and addressing e-waste and 18% pursuing sustainable IT procurement.
The good news is that early signs point to organisations gradually moving toward more advanced capabilities. More than a fifth (23%) are either piloting or implementing Agentic AI (or systems that can act autonomously on insights) across their operations, with 5% deploying it for sustainability purposes.
"Predictive AI anticipates risks, while agentic AI responds in real time, turning strategy into execution. When technology and business strategy align, organisations can truly embed measurable environmental outcomes into everyday operations," says Sash Mukherjee, vice president of industry insights at Ecosystm.
