Digitalisation

By 2030, AI will necessitate a $7 trillion investment in data centers, driven by widespread AI adoption and geopolitical priorities. The demand for specialized compute hardware and energy-intensive AI workloads is creating significant power and supply chain challenges, emphasizing the need for efficiency, renewable energy, and advanced demand forecasting.

The paper highlights the revolution of motor systems through digital technologies enhancing efficiency, despite challenges such as lack of standardization and cybersecurity risks. Innovations include smart sensors, IoT, and AI-driven analytics, with case studies showing significant energy savings. Opportunities exist for professionals in data science and cybersecurity.

The paper discusses the challenges cities face in transitioning to a circular economy, emphasizing the decline in global circularity and the need for public procurement to drive the change. It highlights the complexity of accessing and applying circular strategies and proposes innovation procurement with specialized AI as a solution.

The CORALIS project examines data exchange in industrial symbiosis networks, identifying lack of standardization and proposing a structured communication framework to improve trust, efficiency, and innovation for sustainable industrial practices.

A discussion of the challenge of managing information for industrial symbiosis, focusing on digital tools developed for matchmaking and economic assessment. It underlines the importance of integrating technology with human relationships and adapting to regulatory changes that promote data standardization and transparency.

Industrial symbiosis (IS) promotes sustainability via resource-sharing among firms, yet faces challenges in implementation due to economic, regulatory, and technological barriers. Future success depends on innovation, policy support, and cross-sector collaboration to overcome these hurdles.

European industries use digital tools for energy efficiency, as per a report with nine case studies, highlighting big data, AI for maintenance, demand response programs, collaboration importance, addressing high costs, and skill gaps, offering guidance for integrating technologies and fostering innovation for sustainability.

The IEA's Global Conference on Energy and AI highlighted the reciprocal relationship between both fields, focusing on AI's role in optimizing energy use and enhancing renewable energy adoption, while also acknowledging AI's growing energy demands. Key discussions addressed electricity consumption by data centers, advancements in battery tech, smart grid optimization, predictive capabilities for natural disasters, and international perspectives from companies and governments on AI-driven energy strategies. The IEA stressed its commitment to providing actionable data and fostering stakeholder dialogue to align AI with energy system realities, and announced a comprehensive energy-AI report for 2025.

The Global AI Infrastructure Investment Partnership, with $30 billion from Microsoft, BlackRock, and others, aims to build AI data centers and related energy infrastructure, addressing the high energy demands of AI. Other initiatives like Google's AI Opportunity Fund and IndiaAI Mission support AI infrastructure development, focusing on sustainability and international cooperation to ensure global economic and technological advancement.