APPEC: Energy, shipping experts urge usage of AI as a tool, not as captain

The adoption of artificial intelligence among energy and shipping companies is growing steadily, helping to reduce operational costs, boost productivity, and reduce emissions, but a shortage of skills, data integration complexity, and trust are posing some of the major challenges, industry leaders attending APPEC said.

While the use of AI in sectors, such as upstream, will see robust growth due to uncertainties linked to exploration and prospecting, AI is rapidly becoming a powerful enabler for the maritime sector — from analyzing safety and compliance data to optimizing voyage planning and port logistics, as well as assessing weather and maintenance risks, they added.

"The oil and gas industry is no stranger to cycles of transformation. Today, AI is no longer an experiment at the edges -- it is beginning to reshape core operations across the value chain," Arun Biswas, strategic engagements leader at IBM Consulting for Asia-Pacific, told APPEC 2025 in Singapore, hosted by S&P Global Energy.

Highlighting a recent AI survey undertaken by IBM for the energy industry, he said that more than 40% of companies have AI in play across upstream, midstream, and downstream operations.

"While only 5% have fully scaled AI, many are moving from pilots (15%) into broader rollout (10%). Use cases span asset management, operational efficiency, and customer service - with emerging traction in environment, health, and safety," he said.

Where implemented, AI has helped to decrease operating costs by 18%, as well as led to a 15% reduction in capital expenditure. 27% improvement in production uptime, 29% fewer operational incidents, and 15% reduction in carbon emissions, he quoted from the survey, adding that 5% of current oil and gas revenues are directly attributable to AI, and it is set to grow to 7% in the next three years.

Across the value chain

Highlighting one of the findings in the Middle East, Biswas said, AI boosted asset failure prediction accuracy to 90% across critical equipment.

In exploration, AI solutions are helping geoscientists analyze complex sub-surface data and improve success rates in identifying drilling sites, cutting time and cost of exploration. In midstream logistics, it helps to optimize complex route planning across midstream logistics operations. And lastly, by deploying AI across refinery operations, oil companies are able to achieve 3%–5% higher yields in high-value fuels while cutting energy use by up to 15%, Biswas said.

Yet challenges persist -- 75% of AI projects still fail to deliver return on investment. The barriers are clear -- data quality, high cost, integration complexity, skills shortages, adoption, and concerns related to trust in AI, Biswas added.

"AI in oil and gas is crossing the threshold from promise to performance. Those who scale successfully will not only achieve efficiency gains but unlock new revenue models, strengthen resilience, and advance sustainability," he added.

According to S&P Global Energy, AI helps to lower individual asset costs by 10%-25%, improving productivity by 3%-8% and increasing energy efficiency by 5%-8%, while easing the path for clean energy investment. Achieving results at an enterprise or industry scale is far more challenging. Navigating regulatory issues, establishing effective partnerships and engendering workforce trust are critical to realizing widespread adoption.

The upstream sector is also able to see the benefits, although there was a need to progress selectively.

The current focus of major international and national energy companies is on understanding the benefits of implementing AI in the areas of digital oilfields through the application of sensors, digital twins, data management, scenario planning, as well as tracking methane emissions. The industry is focused on select use cases with a view to wider portfolio deployment," said Nick Sharma, global head of insights for upstream solutions at S&P Global Energy.

Trust, human intervention

Speakers from the maritime sector also highlighted the opportunities and challenges associated with the adoption of AI.

"AI in shipping isn't a rival -- it is the new radar, unlocking clarity, efficiency, and decisive advantage," Amitabh Panda, managing director at Tata NYK Shipping, told APPEC.

But shipping experts cautioned against overdependence on AI to draw conclusions in a segment which sometimes struggles with lack of systematic datasets. "AI also can be a liability. If we are dependent on faulty datasets and using AI, we will get mess out of a mess," Paolo Tonon, technical director at Berge Bulk, told the conference.

Speakers at APPEC highlighted the importance and urgency of formulating clear regulations regarding deployment strategy and accountability when using AI.

"The key takeaway from some of the shipping experts is that AI is a tool, not the captain. Human expertise and judgement must remain at the helm, supported by ongoing training and real-world experience for seafarers and maritime professionals," said Benjamin Tang, head of liquid bulk at S&P Global Commodities at Sea.