OpenAI is encouraging enterprises to use its new scorecard tool to evaluate the value of AI investments, as competition from low-cost Chinese AI providers intensifies.
SynthePulse Insight · AI deep reading
Version 1 · 1 source
Facing pressure from low-cost Chinese AI providers, OpenAI has released an enterprise AI value assessment framework centered on 'work accomplished,' aiming to change how the industry measures AI return on investment.
In a blog post, OpenAI CFO Sarah Friar points out that traditional software success is measured by 'seats, active users, license renewal rates,' but AI's value requires a more robust metric: 'work accomplished.' The core of this shift is the introduction of the 'Useful Intelligence Per Dollar' metric, focusing on 'the full cost of producing a successful outcome, compared to the value that outcome creates.'
Friar emphasizes that low token cost models don't necessarily deliver high value, as they may take longer to complete tasks than more expensive models, leading to higher total costs. The scorecard requires enterprises to first define what 'completion' means in their operations and compare the approach with and without AI.
First, measure the amount of useful work. Enterprises need to define the standard for 'completion' and compare outcomes before and after AI intervention. Second, calculate the total cost of successful outcomes, including employee time, human review, retries, and rework. Through this method, enterprises can determine which tier of model they need—for example, ChatGPT-5.6's three tiers: Sol (most comprehensive), Terra (mid-range), and Luna (most economical).
Third, evaluate reliability. Accurate and consistent results reduce human intervention, thereby saving costs; Friar calls this 'direct economic value.' Fourth, examine economies of scale: as usage grows, does the investment yield more work output? By tracking outcomes, total costs, and unit costs over time, enterprises can assess whether their AI investment is adding value.
OpenAI's launch of the scorecard comes amid 'growing pressure' from low-cost Chinese AI providers. Meanwhile, a January 2026 PwC study found that only 12% of CEOs believe AI delivers cost and revenue benefits. This data highlights widespread skepticism in the business community about AI return on investment and explains why OpenAI is proactively providing an evaluation tool to drive enterprise adoption.
This article is based on a July 21, 2026 report from AI Business, which primarily paraphrases statements from OpenAI CFO Sarah Friar's blog post. All specific metrics, principles, and background information come from this single source and have not been independently verified by third parties. The PwC study data is mentioned in the report but no link to the original report is provided.
OpenAI's scorecard attempts to shift AI value assessment from a 'cost center' to a 'value center,' but its effectiveness depends on whether enterprises can accurately quantify 'work accomplished' and 'total cost of successful outcomes.' Without independent verification, the framework is currently more of a marketing tool for OpenAI than a validated industry standard.
Primary report
Primary source