Generative AI promises massive efficiency gains—but its high energy consumption raises new sustainability challenges for businesses. Especially in the process industry, with its sensitive infrastructure such as industrial valves, a responsible approach to AI is critical. This article explores how productivity and climate goals can be reconciled.
Generative Artificial Intelligence (AI) is revolutionizing workflows: studies show productivity increases of up to 33%. But this efficiency comes at a cost—energy consumption is significantly higher than that of traditional tools. In energy-intensive sectors like the process industry, where complex infrastructure and the use of industrial valves to control fluid and gas flows are standard, balancing technological progress with climate targets is particularly crucial.
For comparison: a single AI prompt can consume up to ten times more energy than a typical Google search. Multiplied across billions of requests, this results in a substantial CO₂ footprint—depending on the electricity mix, emissions can reach up to 80 grams of CO₂ per query. At the same time, AI significantly accelerates workflows: analyses and decision-making tools—such as those related to the deployment of more efficient industrial valves or maintenance optimization—can now be generated in minutes instead of hours.
Data centers—the backbone of modern AI—produce most of their emissions not during operation, but through the manufacturing and replacement of hardware. Extending hardware lifecycles, using energy-efficient components, and implementing sustainable cooling systems can reduce CO₂ emissions by up to 40%. These strategies align well with the process industry’s typical reliance on long-lasting, robust infrastructure.
Companies like Prior1 are leading the way: with AI-supported analytics, governance frameworks, and 100% green electricity, they combine efficiency with responsibility. Real-time analysis of power and thermal loads in data centers reveals potential for optimization that can be transferred to the process industry—for example, through smart control of industrial valves and reduction of pressure losses.
From 2026, the upcoming EU AI Act will introduce clear guidelines for the environmental evaluation of AI systems. For businesses in regulated sectors such as chemicals, energy, or water management, it will become essential to demonstrate the carbon footprint of their AI solutions.
Conclusion:
The process industry faces a dual challenge—boosting efficiency while meeting ecological standards. AI can be a powerful lever, but only when used consciously, intelligently, and with full consideration of energy sources and system life cycles. The sustainable optimization of components like industrial valves through AI-driven analysis exemplifies how digitalization and decarbonization can go hand in hand.
