AI agents are revolutionizing software by automating tasks and assisting users, but their unique nature presents challenges in monetization due to unpredictable usage patterns and costly operations. Usage-based billing emerges as the most effective strategy for monetizing AI agents, aligning costs with actual usage and providing transparency, fairness, and scalability, as it charges customers based on consumption measured in tokens, API calls, or tasks completed. Platforms like Lago facilitate this model by offering precise usage tracking, real-time billing visibility, and integration capabilities, thus enabling companies to manage complex billing cycles without diverting resources from core product development. Lago's open-source framework provides control and flexibility, helping SaaS teams efficiently implement hybrid pricing strategies and maintain customer trust through clear communication and pilot testing. Effective AI monetization requires not only selecting the right pricing model but also ensuring ongoing evaluation and adaptation to refine billing structures and enhance customer satisfaction.