IFS and PwC UK announced a new whitepaper revealing how Industrial AI is accelerating decarbonization across the world’s most asset-intensive sectors. The report stated that Industrial AI is becoming a critical tool for improving sustainability and operational efficiency while helping organizations reduce emissions at scale.

The findings were released as global decarbonization efforts reach a pivotal moment. Eight hard-to-abate sectors, including aviation, shipping, trucking, steel, cement, aluminum, primary chemicals, and oil and gas, currently account for around 40% of worldwide greenhouse gas emissions. Experts reported that every new industrial furnace or turbine built today risks locking in emissions until mid-century. Therefore, the whitepaper emphasized that optimizing existing assets through Industrial AI is becoming increasingly urgent.

IFS referenced insights from its 2025 research, “The Invisible Revolution,” which surveyed more than 1,700 senior executives across manufacturing, energy, construction, and utilities. The study revealed that Industrial AI adoption is accelerating rapidly. Additionally, 86% of executives believe AI will help organizations achieve environmental goals in areas such as energy efficiency, emissions reporting, and CO₂ management.

The whitepaper reported that Industrial AI is already delivering measurable results across multiple applications.
Key improvements include:
• Field service optimization reducing travel distance by an average of 37%
• AI-driven scheduling decreasing Scope 2 emissions by up to 47.6%
• Predictive maintenance extending asset life and preventing energy waste

Sophie Graham, Chief Sustainability Officer at IFS, said Industrial AI is changing how organizations approach sustainability. She reported that customers are using AI to optimize field service routes and production schedules, resulting in less waste, lower emissions, and stronger operational performance. She added that IFS remains committed to deploying AI solutions that support both sustainability goals and competitiveness.

Leigh Bates, Partner at PwC, said AI holds transformative potential for industrial and hard-to-abate sectors by guiding companies toward net-zero outcomes with greater precision. However, he also noted that the energy demand of AI systems must be managed responsibly to maintain net-positive impact.

The report identified three major pathways where Industrial AI influences sustainability: enabling companies to do more with fewer resources, generating traceable and auditable data to verify progress, and supporting new business models such as circular operations through digital twins and AI-driven decision analytics.

The whitepaper also addressed the AI energy paradox. It reported that while AI adoption increases energy demand, responsible deployment still results in significant net reductions in global emissions. Citing research from the Grantham Research Institute and Systemiq, it revealed that AI-driven advancements across power, transport, and food systems could cut 3.2 to 5.4 billion tonnes of CO₂-equivalent emissions annually by 2035.

The report called for renewable energy sourcing, carbon-aware scheduling, edge computing, and strong data governance to ensure the efficiency gains from Industrial AI outweigh its energy consumption.

A critical insight highlighted was Industrial AI’s ability to produce traceable and auditable data across operations. The report stated this capability is essential as regulators, investors, and customers demand measurable progress on decarbonization.

The whitepaper concluded that organizations should begin with measurable use cases such as predictive maintenance, scheduling optimization, and process control. It added that successful scaling of Industrial AI depends on data readiness, governance, secure infrastructure, and sustainable compute practices. According to the authors, Industrial AI is already reshaping industrial operations, and early adopters will lead the next era of sustainable industry.

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