How to Talk to Your CFO About AI Gateway Metrics (Without Losing Them in the First Slide)
Blog post from Kong
As AI infrastructure generates financial signals that often go unnoticed by CFOs, bridging the gap between technical metrics and financial reporting becomes crucial for effective decision-making. The AI connectivity platform can serve as both a technical and financial control plane, offering insights into token consumption, cache hit rates, and model routing decisions, which are vital for cost management and profitability. This guide emphasizes the importance of translating technical data into financial terms for CFOs, highlighting the need for infrastructure observability to align with financial reporting. It suggests starting conversations with CFOs by focusing on key metrics that reveal cost exposures and margin improvements, ultimately enabling informed financial decisions. The AI gateway captures essential data on workload costs and customer service costs, yet this information often resides in technical observability tools rather than financial reports. By effectively communicating the financial impact of AI operations, organizations can leverage existing systems for enhanced financial visibility, thereby aligning AI initiatives with business objectives and ensuring that finance teams understand the economic implications of AI investments.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 8 | 9,074 | 1,640 | 224 | +53% |
| AI Agents | 4 | 4,942 | 1,264 | 250 | +12% |
| Observability | 4 | 3,421 | 707 | 180 | -24% |
| Real-time | 2 | 5,735 | 1,391 | 247 | -9% |
| Platform Engineering | 1 | 1,288 | 297 | 83 | +19% |