Across the landscape of climate catastrophes and resource depletion, industries are under pressure to move from unsustainable to sustainable legacy systems. The potential of AI for optimizing industrial operations and supply chains to sustain economic development while maintaining the environment must be fully realized through strategic implementation and regulatory support. A well-planned integration of AI technologies (e.g., predictive maintenance, route optimization, and generative design) can offer organizations better efficiency, less waste, and adherence to sustainability standards worldwide. We present a structured five-pillar framework that focuses on technological preparedness, organizational capacity, collaboration with stakeholders, ethical safeguards, and adaptive monitoring to support the implementation of AI. Case studies show real results, with energy costs reduced by 30% and emissions by 25% by leveraging AI across industries. The authors argue for systems thinking addressing sustainability as a complex challenge and that inter- and trans-disciplinary synergies between operations research, environmental science, and organization theory would further the field, only if working together. Ethical factors, such as algorithmic transparency and equitable workforce transitions, are key to addressing risks, including job displacement and greenwashing. Ultimately, AI is not the panacea many of us hope for but rather a strategic enabler for a new post-carbon age that requires, beyond effective policies, inclusive governance and continual innovation to balance profit with planetary health. The framework places AI as an augmenter of resilient circular economies, calling on industries to adopt intelligent transformation as a vital pillar of sustainable evolution.