Asian commodity firms accelerate AI adoption amid challenges

Asian commodity firms are accelerating the adoption of artificial intelligence to enhance decision-making, anticipate market movements and augment supply chain performance; however, fragmented data systems and a shortage of skilled talent have presented some challenges in delivering returns on these investments, according to speakers at the Financial Times Commodities Asia Summit on Dec. 4.

As pressure mounts to improve efficiency, manage risk and boost transparency, the adoption of AI has moved beyond pilot projects to real-world deployment, with commodity market participants in Asia leveraging the technology in areas such as trading, logistics, emissions tracking and production, according to speakers at the conference.

With appropriate training and regulation, Asia's commodities sector could play a pivotal role in driving AI-powered innovation, the speakers said.

"The AI boom, and the investment in infrastructure, is for real," Janet Kong, CEO of Hengli Petrochemical International, told the conference.

Early returns from AI investments in the energy sector have the potential to lower costs by 10%-25%, improve productivity by 3%-8% and increase energy efficiency by 5%-8%, while also facilitating clean energy investments, according to S&P Global.

However, navigating regulatory complexities, building effective partnerships and fostering workforce trust are essential for enabling widespread adoption of the technology, the speakers said.

Commodity trading firms are leveraging AI to analyze past and current market trends, using these insights to identify potential trading opportunities for the future, according to the speakers.

"We are doing a lot of investments in how to enhance AI use at the operational level. I think with the evolution of AI, you will have more of the large language models that will happen within the companies to help them with very particular use cases," said Ioana Matei, chief innovation officer at agricultural merchant and processor Louis Dreyfus Company.

"What we are trying to understand is how these physical signals that we have in our supply chain will help us further enhance our trading decisions," Matei said. "We are upgrading our training programs to say, okay, what does it mean for junior traders or people at entry level to learn before they access these tools that make automatic recommendations."

Production to operations

Singapore-based agri-food company Japfa said it has developed a knowledge base, which has improved operational efficiency across its extensive agri-food network.

"What we have built is actually a knowledge base that is able to kind of suggest to the production team when there is an issue, what are the possible root causes and then based on those root causes, what are the actions you should be taking," said Eu Kwang Chin, chief digitalization officer at Japfa, with a network of farming, processing and distribution facilities in Indonesia, Vietnam, India, Myanmar and Bangladesh.

"With that, I think our production team feels more assured that when they hit the situation, they are given help as required. So, I think that is one of the projects that we have put in place, pushing AI all the way to the front of the operation," he said.

Speakers at the conference emphasized the urgent need to address operational and strategic barriers that hinder the scaling of AI across highly fragmented markets and data ecosystems in both the commodities and energy sectors.

The urgent demand for AI infrastructure has put significant strain on energy resources, according to S&P Global, leading organizations to adapt and evolve their sustainability strategies to address these new challenges.

Dave Ernsberger, president of S&P Global Energy, said in a Nov. 27 Platts Oil Markets Podcast, "As the energy industry applies AI, it also needs to find the energy to keep AI going. And that is an interesting conundrum for this cycle of the industry."

"Without a clearer framework, a lot of utilities are worried about stranded investment and stranded costs. And until regulators catch up to these new questions, to be fair to regulators, there could be a lot of lags, not just in regulation, but in investment," Ernsberger said. "And that is because the energy industry, as you may know, has a huge history of big wins, but it also has a long history of stranded cost. And people want to make sure they do not fall on the wrong side of the ledger on that."