• JAGRATI SHRIMALI
• DIVISHA JOSHI
• GAURAV CHOUBISA
• Dr. AJAY KUMAR SHARMA

The productive handling and allocation of resources have become explanatory factors in driving resource optimization, sustainability, and profitability across industries. In Traditional, resource management methods deal with managing the way in which people and natural landscapes interact. In this paper we explore AI-driven strategies for dynamic resource management and optimization, focusing on leveraging artificial intelligence to predict, allocate, and optimize the resource usage in real-time. By integrating data from multiple sources, which includes IoT sensors, past developments, and environmental factors, AI generated systems can help in forecasting demand, identify inefficiencies, and recommend resource allocation strategies that reduces the waste and maximize its value. The research examining different AI techniques, including machine learning, computer vision, predictive analytics, and optimization algorithms, to address key challenges such as sustainability, cost reduction, and scalability. Additionally, the research describes various potential benefits of AI in improving decision-making processes, ensuring more agile or fast responses to resource fluctuations and driving sustainable practices. Through the development and application of these strategies, AI has the capacity to transform how industries manage resources, optimizing operations while minimizing environmental impact. In additionally how AI technologies are used for smarter, more efficient resource management.

Artificial intelligence, Resource Management, Predictive Analytics, Sustainability.

"AI-driven Strategies for Dynamic Resource Management and Optimization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 6, page no.382-388, June-2025, Available :http://www.jetir.org/papers/JETIRGW06064.pdf

"AI-driven Strategies for Dynamic Resource Management and Optimization", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 6, page no. pp382-388, June-2025, Available at : http://www.jetir.org/papers/JETIRGW06064.pdf