Automation and Sustainability—The Impact of AI on Energy Consumption and Other Key Features of Industry 4.0/5.0 Technologies
Source abstract
Abstract
Automation and sustainability are closely intertwined in the evolution of Industry 4.0 and 5.0, where artificial intelligence (AI) plays a key role in transforming energy consumption and production efficiency. For Industry 4.0, AI-based automation has optimized production, logistics, and resource management, reducing waste and improving throughput through predictive analytics and intelligent control systems. These systems have enabled energy-efficient production lines by automatically adjusting processes to minimize downtime and energy consumption. However, the increasing use of AI and digital infrastructure has also led to an increase in demand for computing energy, raising concerns about data center efficiency and carbon footprint, leading to the division between Green AI and Red AI. Industry 5.0 expands this paradigm, focusing on human–machine collaboration and sustainable design, where AI supports personalization, circular economy practices, and the integration of renewable energy. Generative AI and digital twins (DTs) enable real-time energy modeling, helping companies simulate outcomes and choose the most sustainable paths. Automation also enables predictive maintenance, extending machine life and reducing material waste. At the same time, AI is contributing to the development of decentralized energy systems, such as smart grids and microgrids, which increase resilience and reduce emissions. A key challenge is balancing the energy efficiency benefits of automation with the sustainability of the AI infrastructure itself, which requires innovation in energy-efficient computing and green algorithms. From this perspective, AI-based automation represents both a solution and a challenge: it accelerates the achievement of sustainable development goals while requiring responsible technological management to ensure long-term ecological sustainability.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Digital Transformation in Industry · COVID-19 impact on air quality · Internet of Things and AI
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Computer Science, Kazimierz Wielki University, 30 Chodkiewicza St., 85-064 Bydgoszcz, Poland
Faculty of Mechanical Engineering, Poznań University of Technology, Marii Skłodowskiej-Curie 5, 60-965 Poznan, Poland
Faculty of Mechatronics, Kazimierz Wielki University, 30 Chodkiewicza St., 85-064 Bydgoszcz, Poland
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