The fight against climate change is a global concern that continues to face significant challenges. According to the U.S. Energy Information Administration (EIA), a staggering 60% of the energy generated worldwide is wasted. This statistic underscores the urgency of adopting more effective measures to reduce energy consumption and greenhouse gas emissions. In this context, artificial intelligence (AI) emerges as a potentially transformative tool.

A recent report from the EIA reveals that energy consumption in the United States will increase by 2.5% in 2024. Additionally, AI data centers are expected to add around 323 terawatt-hours of electricity demand in the U.S. by 2030. These figures highlight the growing energy demand driven by technology and raise the question: is AI part of the problem or part of the solution? Despite concerns about increased energy consumption, AI has the potential to be a key tool in promoting sustainable strategies. The global AI market in manufacturing is estimated to grow to $20.8 billion by 2028. There are three main areas where AI can optimize energy efficiency and support sustainability goals in manufacturing.

 

AI as a Catalyst for Sustainability

AI can provide dynamic recommendations to adjust energy use based on real-time data. This minimizes waste and reduces the carbon footprint. For example, AI-powered predictive maintenance models can detect inefficiencies in equipment before they become serious problems, ensuring optimal performance and extending asset life.

Additionally, AI has the capability to forecast energy demand patterns with unparalleled accuracy. This allows organizations to optimize energy procurement strategies and effectively balance supply and demand. By analyzing historical consumption data, market trends, and external factors such as weather conditions, AI algorithms can recommend optimal energy mixes, including renewable energies, to meet demand while minimizing costs and environmental impact.

The transition to clean energy sources faces significant challenges, from infrastructure issues to regulatory complexities. AI can streamline processes such as network topology discovery, panel information, and electrical equipment management. Using AI-driven analysis, manufacturers can identify the most viable pathways to integrate renewable energy sources into existing infrastructures and optimize energy distribution and storage.

As more manufacturers adopt AI, they will align sustainable development with business profitability. This will not only increase operational productivity but also improve resilience and environmental management. AI can play a crucial role in creating a world where digital technology and sustainability converge seamlessly.