Modern enterprise companies face significant challenges in revenue forecasting due to the complexity of contemporary pricing models, particularly with the shift towards consumption and usage-based billing structures. These models, which have gained traction in the B2B SaaS sector, offer growth opportunities but also introduce volatility in revenue streams, making traditional forecasting methods insufficient. Companies adopting such pricing strategies report higher revenue growth but struggle with the unpredictability of customer behavior and multiple pricing dimensions. The adoption of consumption-based models necessitates sophisticated data infrastructure and advanced forecasting methodologies, such as cohort-based revenue modeling and AI-powered predictive analytics, to manage billing events and accurately predict future revenue. Platforms like Lago address these challenges by providing real-time metering and billing automation, ensuring precise usage tracking, and enabling seamless data integration across systems. As AI capabilities expand, the future of revenue forecasting will increasingly rely on innovative analytics tools and metering infrastructure to accommodate fluctuating costs and drive pricing innovation.