The third annual Global Sustainability Barometer Study conducted by Ecosystm revealed that 87% of Singaporean businesses are committed to sustainability, significantly higher than the global average of 66%. The study also indicates that only 35% of these organisations are currently leveraging AI to drive their environmental initiatives.
As Singapore gears up to meet stricter climate-related disclosures under the Singapore Exchange (SGX) rules and faces increasing carbon tax pressures, many companies are pushing forward with sustainability efforts. The study shows a marked increase in the alignment between IT and sustainability teams, with 63% reporting strong collaboration compared to just 40% last year.
“Organisations in Singapore are decisively harnessing technology to advance environmental sustainability outcomes. Rising disclosure requirements and increasing pressure for real-time reporting are driving the need for AI, automation, and trusted data platforms,” said Guat Ling Ang, managing director of Kyndryl Singapore. “When sustainability is built into core business operations, businesses can gain clearer insights that help them make smarter, data-driven decisions.”
The report highlights that Singapore’s engagement with integrated sustainability practices is among the highest globally, with 35% of organisations embedding these practices into their core processes, compared to a mere 16% worldwide.
Furthermore, 52% of Singaporean companies are positioning sustainability as a core driver of innovation and cost savings. This sets them apart as leaders in the global context.
Another notable finding is the rising adoption of predictive AI to enhance sustainability outcomes. Sixty-three percent of respondents now use predictive AI to forecast resource usage and emissions, a significant increase from 35% last year. Additionally, organisations focusing on anticipating climate risks saw a rise from 45% to 53%.
Despite the positive developments, challenges persist. The study notes that 52% of organisations cite unclear ROI and data collection hurdles as major barriers, and 50% struggle with integrating data from internal systems. These issues must be addressed for companies to fully leverage AI in driving environmental decisions.
