OpenAI CFO to firms questioning return on AI investments: Don't rush to cheap model
OpenAI CFO Sarah Friar is encouraging corporate leaders to shift their focus from raw AI token costs to a new metric called 'useful intelligence per dollar.' This framework emphasizes measuring the actual value of completed tasks, such as resolved customer issues or shipped code, rather than prioritizing the cheapest available models.
Why it matters
As enterprises face an 'AI cost reckoning,' this shift in measurement is critical for determining whether massive AI investments are delivering sustainable financial returns or merely inflating operational budgets.
As tech company executives grow increasingly anxious over whether their massive artificial intelligence (AI) bills are actually paying off, OpenAI CFO Sarah Friar is pitching a new corporate scorecard to measure the technology’s real success. In a new company blog post (via Axios), Friar urged leaders to stop focusing on sticker prices and token costs. Instead, she argues that businesses should not rush to the cheapest AI models on the market, but should buy the AI tools that maximise performance and value.The framework arrives as Silicon Valley faces a massive enterprise ‘AI cost reckoning’, with corporate CFOs demanding clearer returns on their investments.
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