Transformative responses beyond traditional sustainability are imperative in the face of a rapidly accelerating climate crisis. We introduce the concept of digital photosynthesis, a design paradigm in which artificial intelligence (AI) emulates the optimal structure of a natural ecosystem to build a carbon-neutral economy. This framework seeks to build dynamic systems by integrating AI with urban planning (such as smart buildings and transportation systems), sustainable agriculture, and green transportation to improve resource use, reduce emissions, and increase resilience. This cross-sector model integrates technological innovation with ecological values, financial models, and social equity. AI-based smart grids, precise farming type applications, and autonomous networks of electric vehicles have shown datasets from such applications, indicating that AI can decrease urban emissions by up to 70% and reduce agricultural water consumption by approximately 30% during re-engineering logistics. However, ethical risks, including data privacy, algorithmic bias, and inequitable access, must be governed through active mechanisms. This report confirms that AI-enabled sustainability is both possible and critical and hinges on collaboration, policy, and continuous calibration globally. By leveraging AI’s computing power in the service of planetary boundaries, this blueprint reveals a viable path towards a regenerative future.