AI Monetization Challenges - Traditional SaaS pricing models are ineffective for AI-powered products due to unique complexities like fluctuating usage and variable compute costs [1] - Overlooked monetization aspect of AI is critical for businesses [1] Adaptive Pricing Strategies - Adaptive pricing models can drive cost savings, enhance customer experience, and reduce operational bottlenecks [1] - Usage-based, tiered, and hybrid pricing models can maximize revenue potential [1] - Real-time data can be leveraged to test, adjust, and optimize pricing strategies [1] Revenue Simulation and Risk Reduction - Revenue simulations enable companies to test and refine pricing before implementing, reducing risk and boosting adoption [1] - Orb enabled Replit to make pricing changes up to the last minute and provided usage alerts [1] Key Takeaways - Companies should avoid common pricing pitfalls that can lead to revenue leakage and customer churn [1] - Session is designed for AI executives, product leaders, and engineering teams looking for actionable strategies to build adaptive, scalable pricing models [1]