Rippling, the HR software company, has launched AI Spend Console after its internal AI token costs soared into the millions. The new tool provides granular visibility into AI spending by employee, team, and role, linking token usage to measurable work output such as code reviews and pull requests.
The product emerged from a wake-up call in March when Rippling’s finance team discovered that AI tokens could consume 40% of its R&D headcount budget. Monthly spending had grown by 80%, pushing the projected annual cost to nearly 90% of that payroll budget. Chief Product Officer Matt MacInnis said executives were “incredulous” when they saw the figures.
Upon investigation, Rippling found that 10–15% of workers accounted for about 60% of total AI spending. One engineer alone used $50,000 worth of AI tokens in a single month. Employees frequently selected expensive frontier models for routine tasks.
Rather than cutting access, management initiated an urgent cost review. Rippling negotiated spending caps with providers including Cursor, OpenAI, and Anthropic, and built an AI gateway that routes each request to the most cost-effective model based on task complexity and cost.
The changes reduced token spending from 40% of Rippling’s R&D headcount budget to about 15%. Usage remained near peak levels: 605 billion tokens in April and 600 billion in July, yet July’s bill was only 37% of April’s cost. CEO Parker Conrad noted that GLM 5.2 cost 85% less while delivering nearly comparable results for their tasks.
AI Spend Console combines prompt volume, model costs, and work data in a single dashboard. For engineers, it compares spending with code output, pull requests, and review results. Managers can identify employees whose costly AI work frequently requires revision. Rippling also appointed “AI captains”—power users who help colleagues apply AI to suitable tasks.
The console is included with Rippling’s HR subscriptions, though customers pay additional usage-based AI fees. It can also be purchased separately and connected to another HR system, tracking spending at individual, team, and role levels within the same workforce data structure.