Orb convened a diverse group of industry leaders to discuss the challenges of integrating AI into various sectors, highlighting the AI pricing dilemma where the volatility in AI-powered product costs contrasts with customer demands for predictable pricing. This tension is exacerbated by traditional fixed-cost models giving way to variable costs and tighter margins, making it difficult for companies to balance technical realities with buyer expectations. Usage-based and credit systems introduce unpredictability, complicating budgeting for both vendors and non-technical buyers who prefer pricing tied to tangible business metrics. Competitive pressures further strain margins, with AI model and hardware costs frequently fluctuating. As a result, companies are exploring alternative pricing models like "human replacement" and outcome-based pricing to align costs with perceived value, though these approaches can be operationally complex. The complexities of AI pricing also affect performance measurement, as traditional metrics like ARR often fail to capture the full revenue picture, leading to a call for new standards. The roundtable underscored that AI pricing challenges are now a universal issue, prompting companies like Orb to develop strategies that balance dynamic pricing with customer expectations while maintaining financial transparency.