Equipping workers with insights about compensation
Source: OpenAI Blog
Introduction
Wage information shapes important decisions: what jobs people apply for, whether they negotiate, and whether a particular career path is worth pursuing. Unlike the price of most goods, the price of labor is often hard to find and difficult to interpret—especially for workers who are early in their careers, switching fields, or moving locations.
AI is a new type of labor‑market resource. Rather than requiring a worker to search across multiple websites, interpret scattered salary pages, or ask a socially risky question, a model can synthesize wage information and return a benchmark in seconds. Workers are already using ChatGPT this way, sending nearly 3 million messages per day, on average in the US, asking about wages, compensation, or earnings.
Research Findings
Our latest research report (opens in a new window) examines how Americans are using ChatGPT to close the wage‑information gap. Users most often come to ChatGPT for two kinds of help:
- Translating pay into a usable benchmark
- Understanding what a role, company, career path, or business idea might realistically pay
Among labeled wage‑benchmarking messages, the distribution of question types is:
| Question type | Share of messages |
|---|---|
| Pay calculation | 26 % |
| Specific role | 19 % |
| Entrepreneurship | 18 % |
| Specific role at a company | 11 % |
| Occupation or career questions | 11 % |
These insights were derived through a privacy‑preserving analysis that uses automated classifiers and never involves a human viewing individual messages.
Occupation‑related searches
Occupation‑related wage searches are concentrated in:
- Arts, design, entertainment, sports, and media
- Management
- Healthcare
- Transportation
- Sales
- Business and financial operations
Relative to overall employment, wage searches over‑index in higher‑skill and less transparent occupations such as creative fields, management, healthcare, and computer‑mathematical roles. This suggests demand is strongest where pay is harder to benchmark, more negotiable, or more important to career mobility.
Entrepreneurship‑related searches
Entrepreneurship‑related questions cluster around creative work and small service businesses—areas where posted wage benchmarks are often absent.
Cross‑industry patterns
Across industries, wage search rises where pay is more dispersed and where wages are higher. Workers tend to seek pay information most when:
- Getting the answer right matters more
- Pay is harder to read
Misunderstanding potential earnings can keep workers in lower‑paying jobs, undercut negotiating power, delay career moves, or discourage investment in education and training. Better information cannot eliminate uncertainty, but it can help people form a reasonable view of what work pays and make better decisions.
WorkerBench Benchmark
To better understand how our models serve workers, the report introduces WorkerBench, a new effort to evaluate ChatGPT on labor‑market tasks valuable to workers. In this first benchmark:
- GPT‑5.4 was evaluated against 2024 OEWS median wages at the national occupation and metro levels.
- The observed sample showed the model is highly accurate: coverage is high, bias is small, and almost all numeric estimates fall very close to the benchmark.
Conclusion
Pay information is economically important but often difficult or sensitive to obtain. Workers are already using ChatGPT to navigate that problem, especially in parts of the labor market where uncertainty is highest and the stakes are most meaningful. Our goal is to keep improving how useful and reliable that help can be—moving beyond national benchmarks toward the geography, firm, level, and compensation questions workers actually ask every day.