IFS has released a new whitepaper on the important role Industrial AI can play in the decarbonization of the world’s most asset-intensive industries. “The Intelligence Behind Sustainability: Industrial AI’s Critical Role in Decarbonization” calls on the industrial world to leverage Industrial AI to improve sustainability and operational efficiency, supporting measurable emissions reductions across heavy and hard-to-abate sectors.
The report arrives at a critical juncture for global decarbonization efforts. Eight hard-to-abate sectors including aviation, shipping, trucking, steel, cement, aluminum, primary chemicals, and oil and gas, account for approximately 40% of total global greenhouse gas emissions. With every new furnace or turbine built today risking locked-in emissions until mid-century, the need for intelligent optimization of existing assets, as well as transition to new operating models, has never been more urgent.
Drawing on IFS’s research, “The Invisible Revolution” (2025), which surveyed more than 1,700 senior executives globally across manufacturing, energy, construction, and utilities, the report reveals that industrial AI adoption is accelerating rapidly and 86% believe AI will help organizations meet environmental goals from energy efficiency and emissions reporting to CO₂ management.
Industrial AI is already delivering measurable results. The report documents how AI-driven solutions are cutting emissions and costs across multiple applications:
- Field service optimization reducing travel distance by an average of 37%, delivering measurable efficiency gains and supporting emissions reduction efforts, according to IFS field service data
- AI-driven scheduling can support reductions in Scope 2 emissions by up to 47.6% by aligning production with periods of lower grid carbon intensity
- Predictive maintenance is extending asset life, reducing embodied carbon, and preventing energy waste from equipment failures
“We’re seeing Industrial AI fundamentally change how organizations approach sustainability,” said Sophie Graham, Chief Sustainability Officer at IFS. “Our customers are using AI to optimize everything from field service routes to production scheduling, and the results are tangible: less waste, lower emissions, and stronger operational performance. At IFS, we’re committed to deploying AI solutions that help our customers achieve their sustainability goals while building more resilient, competitive operations.”
“AI holds transformative potential for industrial and hard-to-abate sectors, guiding us towards net zero outcomes with innovative precision. However, as AI-driven solutions illuminate our path, we must also manage their energy demand responsibly. Harnessing this dual opportunity to lead with sustainability and efficiency will be at the forefront of industry evolution,” said Leigh Bates, Partner at PwC.
Three Pathways to Sustainability Impact
The report identifies three key ways industrial AI intersects with sustainability. First, it enables industrial organizations to “do more with less” by optimizing resource use and reducing waste across operations. Second, it allows companies to leverage data for insights, creating traceable, auditable information that verifies sustainability results and supports decision-making. Third, it delivers business model transformation by enabling outcome-based and circular economy models through digital twins and AI-driven decision analytics platforms that help organizations test long-term investment portfolios against climate scenarios.
Addressing the AI Energy Paradox
While acknowledging that AI adoption comes with increased energy demand, the report emphasizes the net positive impact when responsibly deployed. According to research from the Grantham Research Institute on Climate Change and the Environment and Systemiq, advancements in AI in power, transport, and food consumption could reduce global greenhouse gas emissions by 3.2 to 5.4 billion tonnes of carbon-dioxide-equivalent annually by 2035.
The report calls for a balanced approach that includes renewable energy sourcing, carbon-aware scheduling, edge computing, and strong governance over data quality and validation to ensure AI’s energy use doesn’t erode the gains it delivers.
A critical finding highlighted in the report is Industrial AI’s unique role in creating traceable, auditable data across operations. This capability addresses the growing demand for measurable, verifiable decarbonization progress from regulators, investors, and customers seeking to decarbonize their value chains.
The report concludes that organizations must start with measurable use cases like predictive maintenance, scheduling optimization, and process control that deliver fast returns. Success requires investing in data readiness to ensure clean, connected data supports scalability, while embedding trust early through governance, secure infrastructure, and sustainable compute practices. Industrial AI is actively transforming operations today. The organizations embracing it first will lead the next era of sustainable industry.
