This document presents AI-RAN, a paradigm shift integrating Radio Access Network (RAN) and Artificial Intelligence (AI) workloads onto a unified platform. It outlines the evolution of RAN and categorizes AI-RAN into three forms: AI-for-RAN, AI-on-RAN, and AI-and-RAN. The paper identifies key requirements and enablers for this convergence, including accelerated computing and cloud-native design. A proposed reference architecture is provided, and a proof-of-concept utilizing NVIDIA Grace-Hopper servers demonstrates the potential for concurrent workload processing and improved asset utilization. Finally, the document concludes with future work directions for AI-RAN.