AI and data analytics for sustainability: A strategic framework for risk management in energy and business

Adetumi Adewumi 1, *, Chioma Susan Nwaimo 1, Daniel Ajiga 2, Mercy Odochi Agho 3 and Kate Aigbaifie Iwe 3

1 Independent Researcher, Illinois, USA.
2 Independent Researcher, Seattle, USA.
3 Independent Researcher, Port Harcourt, Nigeria.
 
Review
International Journal of Science and Research Archive, 2023, 08(02), 767–773.
Article DOI: 10.30574/ijsra.2023.8.2.0158
Publication history: 
Received on 11 January 2023; revised on 20 April 2023; accepted on 24 April 2023
 
Abstract: 
This paper explores the integration of artificial intelligence (AI) and data analytics in promoting sustainability and enhancing risk management within the energy and business sectors. It highlights the role of AI technologies in driving energy efficiency and sustainable practices, demonstrating how predictive analytics can optimize energy usage and integrate renewable energy sources. The significance of data analytics in risk mitigation and strategic planning is discussed, showcasing its capacity to provide data-driven insights for proactive risk management. Furthermore, the paper outlines AI-driven models for predictive analytics in energy systems, emphasizing their benefits in forecasting, operational optimization, and sustainability. Recommendations for implementing AI and data analytics in sustainability initiatives are provided, focusing on investment in data infrastructure, fostering a data-driven culture, scalable solutions, interdisciplinary collaboration, ethical practices, and regulatory compliance. The paper concludes by underscoring the transformative potential of AI and data analytics in achieving sustainability goals and improving resilience in the energy and business sectors.
 
Keywords: 
AI in Energy Efficiency; Data Analytics; Sustainability; Risk Management; Predictive Analytics; Renewable Energy Integration
 
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