As the maritime industry accelerates toward a green future, Wind-Assisted Ship Propulsion (WASP) offers a critical pathway for emission reduction. However, realizing the full potential of WASP technologies requires advanced Digital Twin frameworks capable of mirroring the complex, stochastic interactions between the hull, wind-devices, and the environment. The current state-of-the-art largely decouples these physics, evaluating devices in idealized flat water or steady wind, thereby missing the critical nonlinearities of realistic operation at sea. This work presents a breakthrough digital simulator that overcomes these limitations by integrating unsteady Computational Fluid Dynamics (CFD) with a generative AI environmental model. Unlike traditional spectral methods, the generative AI uniquely synthesizes physically consistent, joint wind-wave environments, enabling the simulation of the fully nonlinear, coupled interaction between the hull, propeller, rotors, and the dynamic seaway. Leveraging this AI-enabled fidelity, we investigate the critical coupling between wave-induced motions and rotor performance. The simulation reveals that large-amplitude roll and pitch introduce significant velocity fluctuations along the rotor that disrupt the ideal flow state. We use the GenAI enhanced CFD simulator to quantify the resulting unsteady aerodynamic phenomena, specifically dynamic inflow distortion and hysteresis in Magnus force generation, which deviate significantly from quasi-steady predictions. This methodology advances the frontier of sustainable marine engineering, providing a physics- based data-driven tool for the lifecycle optimization and continuous monitoring of next-generation wind-propulsion technologies.