OpenAI GPT 6.1 Sol Pro

Write a briefing for a non-technical executive explaining why their company's spending on AI is hard to predict, and what they can do about it. Cover at least three distinct causes. Plain prose only — no headings, bullet points, or markdown formatting. Write exactly 205 words.

AI spending is hard to predict because the bill depends on how people use the system, not just how many employees have access. A short question costs less than a long conversation, and features that search documents, generate images, or repeat failed tasks can multiply usage unexpectedly. Prices also vary across providers and models. Teams may switch to more capable, expensive models as expectations rise, while discounts, contract terms, and currency movements change the effective price. Rapid product development makes last year’s budget a weak guide. A third source of uncertainty is the work around the technology. Cleaning company data, connecting systems, testing accuracy, protecting sensitive information, and training staff can cost more than the AI subscription itself. Early pilots often hide these expenses. Finally, successful tools attract demand. A pilot can spread quickly across departments, turning a small experiment into an ongoing operating expense. Manage this uncertainty by budgeting for scenarios rather than one forecast. Track costs by team and business purpose, set usage limits and alerts, and require approval before expanding pilots. Use cheaper models when they meet quality requirements, negotiate clear pricing, and review spending monthly. Judge investments by measurable business outcomes, not adoption alone, and retain flexibility to stop underperforming projects.