This chapter analyzes the economic implications of incorporating AIArtificial Intelligence (AI) into environmental management within India's industrial sector. Regulatory obstacles, insufficient technical expertise, elevated implementation expenses, and inadequate infrastructure impede the extensive adoption of AI in manufacturing, notwithstanding the technology's significant potential for enhancing resource efficiency, mitigating pollution, and promoting sustainabilitySustainability. This study aims to address the gap by analyzing the essential success factors for AI in this context from an economic viewpoint. A total of 254 participants from diverse industrial enterprises in India were surveyed. The research analyzed the interconnections among significant variablesSEM utilizing PLS-SEMPLS-SEM, or Partial Least Squares Structural Equation Modeling. Economic incentives, legal backing, organizational preparedness, data accessibility and integrity, technical competencies, implementation expenses, and other pertinent elements are highlighted as essential determinants for AI adoption. The report emphasizes the necessity of tackling challenges associated with cost, infrastructure, data accessibility, and organizational readiness to fully harness the transformative potential of AI in environmental management. It moreover necessitates a legislative framework that is more accommodating and targeted funds to promote the utilization of AI. This paper fills a critical gap in the literature by presenting a comprehensive technique for quantifying the potential financial advantages of AI technologies in green efforts. Individuals engaged in the field, legislators, and scholars can all derive significant advantages from these results. The findings indicate a favorable potential for employing AI in sustainable environmental management, contingent upon the resolution of existing issues and the establishment of appropriate conditions for its implementation.