Is Consumption-Based AI Pricing Setting Enterprises Up for Long-Term Cost Overruns?

Adam Mansfield of UpperEdge breaks down a critical but overlooked risk in today’s AI deals: token-based, credit-based, and usage-driven pricing models from vendors like OpenAI (ChatGPT), Anthropic Claude, Google Gemini, Salesforce Agentforce, ServiceNow, and Microsoft Copilot Studio.As organizations rapidly adopt generative AI platforms, many are locking into commercial constructs without fully understanding usage definitions, token drawdowns, governance controls, metering thresholds, and renewal leverage risks.What happens when consumption accelerates?What happens at renewal when you're fully embedded?What leverage do you really have?Adam explains why AI may become more expensive than planned, and potentially more costly than the employees it was meant to augment or replace, if enterprises fail to negotiate proper protections, flexibility, and contractual clarity upfront.If you're involved in AI procurement, enterprise software negotiations, or technology strategy, this is essential viewing.Topics Covered:• Consumption-based AI pricing risks• Token and credit model pitfalls• Renewal leverage concerns• Governance and metering controls• Commercial protections in AI contracts• Enterprise AI negotiation strategyLearn how to avoid long-term AI cost traps before your flywheel starts spinning.