Why AI token costs don’t tell you if your AI is working

In an era of rapidly increasing AI usage and declining per-token costs, the disconnect between AI token consumption and delivered value poses a significant challenge for companies like Uber, which have experienced rising AI expenditures without a clear link to productive outcomes. This discrepancy arises because AI costs are traditionally measured in tokens, while value emerges from tangible results such as shipped features or resolved support tickets. The article advocates for a shift to "cost per outcome" metrics, which more accurately relate AI spending to successful results, thereby providing actionable insights into the effectiveness of AI investments. This approach involves capturing and evaluating AI tasks to determine their actual success, allowing businesses to make informed decisions about optimizing their AI resource allocation. Despite the ongoing token price war suggesting cheaper AI capabilities, the real measure of AI's return on investment lies in its ability to deliver outcomes that outweigh costs.

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