Despite proliferating AI ethics frameworks and regulatory guidance, translating Responsible AI into organizational practice remains inconsistent, particularly among resource-constrained small- and mid-sized enterprises (SMEs) and public institutions. Existing models are either overly abstract or prohibitively resource-intensive. This paper advances a Lightweight Ethics-by-Design Playbook that operationalizes Responsible AI principles—fairness, accountability, transparency, and human oversight—into practical governance triggers, decision templates, and stage-specific checklists aligned with common organizational workflows. Unlike prevailing frameworks, this approach emphasizes scalability, accessibility, and sectoral adaptability without requiring technical infrastructure, empirical validation, or costly certification. By situating the playbook within regulatory debates and illustrating applications in healthcare, financial services, and government AI, the paper contributes a replicable, adoption-ready model bridging aspirational principles and actionable practice.