Sustainability LIVE Singapore: AI in Sustainability Panel
Speaking at Sustainability LIVE Singapore, a panel of leading voices came together to examine the rapidly expanding role of artificial intelligence in sustainability.
Panellists included:
- Terence L Jeyaretnam, Associate Professor at Monash Business School
- Jackson Burnie, Regional Sustainability Lead, APAC at Workiva
- Stuart Scott, Sustainability Practice Leader, Asia Pacific at dss+
Terence opened the discussion by highlighting how AI is already powering progress in multiple sectors – from air quality monitoring and biodiversity tracking to supply chain optimisation.
"If you look at the production chain, if you can reduce defects and improve quality, you have a lower footprint," he said.
Referencing the I=PAT equation (Impact = Population × Affluence × Technology), Terence argued that technology is the key lever left to reduce environmental impact.
"Population and affluence are trending upwards. Technology is our only tool to bring the impact down,” he said.
Jackson agreed, pointing to the practical role AI plays in helping businesses comply with new regulations, particularly IFRS-aligned sustainability disclosure standards.
"AI tools make new topics accessible to everyone," he said. Whether calculating Scope 3 emissions or creating transparent reports, AI is helping businesses overcome knowledge gaps and accelerate action.
Stuart added that the aggregation of sustainability data is where AI can have the most transformational impact.
“Climate modelling, smart grid optimisation, and methane tracking are all dependent on high-quality, large-scale data – and AI helps make sense of it,” he said.
Use cases from climate tech to compliance
Throughout the session, panellists offered real-world examples of AI in action.
Stuart highlighted methane tracking as a high-impact application.
“It’s one of the most potent greenhouse gases,” he said. With satellite and aerial monitoring enhanced by AI, it's now possible to detect and quantify leaks across industries – from gas and mining to agriculture – enabling faster fixes and financial savings.
Terence pointed to Google DeepMind’s AI weather forecasting system, which can predict extreme weather with 20% more accuracy and up to 15 days in advance.
“This is about mitigating large-scale disaster impacts,” he noted.
Both Terence and Jackson also discussed the power of AI in Scope 3 emissions management. As Jackson explained, large suppliers often already disclose their emissions publicly. AI can scrape and match this data to an organisation’s procurement records, reducing the need for manual outreach.
“Instead of sending emails asking for emissions data, AI can map disclosures to your footprint directly,” he said.
On the social side, Terence shared how satellite tech and AI are being used by the Australian Conservation Foundation to identify illegal logging in real-time, with gamers flagging new incidents for enforcement.
“It stopped a major illegal logging event in Queensland last year,” he said.
Challenges of ethics, energy and access
But the panel didn’t shy away from the risks.
Stuart stressed that AI is only as good as the data it receives. Inconsistent or incomplete datasets can undermine its usefulness. He advised businesses to start by defining their reporting outputs and tracing backwards to identify data gaps.
“Think about the end point first, then build your data flow to support it.”
Terence raised deeper ethical concerns. The energy and water required to run AI models are significant, and labour practices behind training models also matter.
“We’ve seen cases where low-paid workers in Kenya were training ChatGPT models. Human rights risks are real,” he warned.
There’s also the risk that AI will normalise the status quo.
“What if AI had been trained when the slave trade was legal? It would treat that as normal,” he said. As AI becomes more powerful, it risks reinforcing existing societal inequalities unless diversified data sources and inclusive model design are prioritised.
Jackson added that validation and security are key.
“Organisations can’t rely on hallucinated facts,” he said, calling for stronger safeguards around data privacy. He also warned against AI greenwashing – the use of flashy AI tools to appear sustainable without actually delivering change.
Advice for getting started and staying ethical
As the session wrapped up, panellists offered guidance for businesses looking to use AI responsibly.
“Start with your material topics,” advised Stuart. Whether you're targeting emissions reduction or energy efficiency, identify what matters most and apply AI where it creates real value.
“Don’t automate a broken process. Fix the fundamentals first,” he added.
Jackson championed AI’s power to democratise sustainability understanding.
“Not everyone knows the difference between Scope 1 and Scope 3. AI can break those barriers and help people engage.”
Terence concluded with a call for more diverse data.
“We need inputs from around the world—not just the US and Europe. That’s how we ensure AI reflects real, global values,” he said.
On the human side, the panel agreed AI should augment people, not replace them. Used wisely, it can enhance productivity, empower workers and surface insights that fuel innovation. But the journey must be intentional.
“AI holds huge promise,” said Jackson, “but it has to be part of a plan – not a replacement for one.”
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