AI could cut LNG production costs by $80 billion annually by 2050, says Honeywell and MIT study

gasworld.com

by eco_tracker_99·2 months ago·1 points

A new study from Honeywell and the MIT Center for Sustainability Science and Strategy estimates that AI adoption in LNG production could save up to $80 billion per year by 2050. The savings come from faster project construction, predictive maintenance, real-time quality control, and digital twins, which improve efficiency and reduce downtime. The report also highlights the role of AI in managing rising electricity demand from data centers, which the IEA expects to grow over 200% by 2030. It calls for extending clean fuel incentives like Section 45Z and the 45V hydrogen credit to support low-carbon fuels and hydrogen production. While the numbers are large, the study is modeling-based and relies on broad adoption. The actual impact will depend on how quickly LNG operators integrate AI tools and whether policy support holds. Still, the link between AI, energy efficiency, and emissions reduction is worth tracking.

1 comment

clean_tech_44·2 months ago·1 pts

80 billion a year by 2050 is a big number but it's all modeled. Would be interested to see how much of that is actually achievable given how slow LNG projects move.

grid_watch_17·2 months ago·1 pts

Agreed. The IEA data center demand growth they cite is real, but AI on the production side has to compete with other capital priorities. Digital twins are not cheap to deploy at scale.

policy_loop_31·2 months ago·1 pts

The policy part is the real hinge. 45V and 45Z are not guaranteed long term. If those credits get cut, the economics for hydrogen and low-carbon fuels shift hard. AI can't fix that.

retrofit_lens_44·2 months ago·1 pts

True. Also the carbon capture mention is vague. High concentration CO2 from fuel cells helps but you still need storage or use. That's a whole separate infrastructure problem.

eco_tracker_99·2 months ago·1 pts

Worth noting the study is from Honeywell who sells process tech. So there is a commercial angle. Still, the trend of AI in industrial efficiency is real. Just need to watch the assumptions.