Abstract: The advent of Artificial Intelligence AI, over the years from the initial rule-based system to the present machine learning stages has contributed to the development of technology, and while there are some drawbacks in their exponential expansion, so are several positives. This necessitates the assessment of the strategy as the world moves more to the development and use of AI. Hence, the introduction of regenerative AI, as an alternative in the present system to entirely make good use of the AI potential and at the same time encourage ethical growth, and environmental restoration at the same time allowing beneficial social effects. This work investigates the need to balance the use of AI’s potential in moving innovation and advancement and find a way to mitigate the potential negative consequences on society and the environment in general, including the computational demands of sophisticated AI models together with the resource-intensive training process that contributed to a substantial carbon footprint and the ethical issue that constitute another facet of the problems being faced. The research employs a multifaceted methodology to develop and evaluate the Regenerative AI framework. The Regenerative AI model integrates ethical principles through fairness-aware algorithms, transparency mechanisms, and accountability frameworks. Environmental sustainability is addressed by optimizing algorithms for energy efficiency and exploring renewable energy sources for computations. The results of the study demonstrate the feasibility and efficacy of the Regenerative AI framework. Energy consumption in AI computations is significantly reduced, contributing to a more sustainable AI ecosystem.