Artificial intelligence–driven energy systems for accelerating sustainable development in business

Abstract

Artificial intelligence (AI) technologies have become revolutionary in helping the intelligent management of energy and making decisions in real-time for modern energy systems. This research focuses on artificial intelligence-based energy systems and enables sustainable business development through optimizing energy, predicting renewable energies and smart operating control. A mixed-method approach was adopted, which involved a combination of literature synthesis of AI applications, machine learning modelling of energy prediction, and statistical analysis of the optimization scenarios. The results suggest that energy consumption in the commercial and industrial sectors can be saved by about 15-30% through AI-based energy management systems, and the accuracy of forecasting the use of renewable energies can be increased by more than 90%. Furthermore, smart energy platforms that use AI make it possible to have predictive maintenance, automated demand response, and better integration of renewable energy resources. These capabilities are part of the reduced operational costs and measurable carbon emission reductions to support corporate sustainability strategies as well as global sustainability targets, especially SDG 7 and SDG 12. The increasing energy consumption demands of AI infrastructure, as well as data centers, make it necessary to have stringent regimes around governance and "net-sustainability". Future research must focus on the integration of AI with digital twins, energy storage systems, and blockchain-enabled markets, for realizing a secure and sustainable business energy ecosystem.