Honeywell, working with the MIT Center for Sustainability Science and Strategy, has released new research arguing that artificial intelligence could sharply cut the cost of global fuel production while boosting energy output from existing infrastructure.

 

The study, titled Accelerating Energy Expansion, focuses on how AI-enabled tools can reshape traditional oil, gas, and LNG systems by improving efficiency, reliability, and asset performance—without waiting for large-scale new energy projects to come online.

 

According to the modeling, the financial impact could be substantial. AI applications in traditional oil-based fuel production are projected to reduce global prices could decline by as much as 4.5% over the long term, depending on adoption.

 

Energy leaders behind the report say the opportunity lies in maximizing existing infrastructure.

 

“Meeting the world’s growing energy needs will require both investment in new technologies to broaden feedstock options and more efficient use of today’s energy infrastructure,” said Ken West of Honeywell’s process technology business.

 

“Honeywell is helping customers apply AI, automation, digital and connected solutions to help get more out of their existing assets while also increasing reliability and throughput. The MIT analysis highlights the significant cost-reduction opportunities AI-enabled technologies can unlock in fuel production, which is top of mind for consumers and policymakers alike as we navigate increasingly complex geopolitical dynamics.”

 

The report also highlights rising electricity demand—particularly from AI infrastructure—as a growing pressure point for global grids, arguing that faster, distributed energy solutions will be essential in the near term.

 

“Energy demand is rising quickly, and many organizations are looking for practical ways to add power without waiting years for new generation to come online,” said Jim Masso, who leads the process automation business of the engineering giant.

 

“On-site power generation and energy storage can help operators add capacity where it’s needed most, helping to support the growing demands of AI infrastructure and reduce reliance on already stretched grids. As a result, this enables them to scale more quickly and efficiently.”

 

Beyond efficiency gains, the study emphasizes energy diversification as a pillar of long-term security. It points to alternative fuels such as sustainable aviation fuel, and the use of regional feedstocks like biomass, waste oils, and non-edible crops to reduce import dependence and improve resilience.

 

The overall conclusion is clear: the fastest gains in global energy capacity may come not from entirely new systems, but from using AI and digital tools to extract more value from what already exists—while gradually expanding and diversifying the energy mix.