Opportunity Data is an independent research platform that brings together credential earnings, AI exposure scoring, and higher education accountability research.
Public data sources. Fully reproducible. Built with students and learners in mind, for institutions, policymakers, and workforce leaders.
Explore the platformThree interactive toolsets, each grounded in public federal data and reproducible end-to-end.
Which occupations are most exposed to A.I. automation, and which academic programs feed into them? Three-dimensional scoring across digital intensity, human interaction, and physical work. 772 occupations, 1,786 programs.
From eligibility screening to state implementation. Approximate the federal earnings test program by program, track each governor's progress in standing up the approval pipeline, and read how the threshold is constructed.
What graduates actually earn at 1, 5, and 10 years, drawn from Census Bureau administrative wage records. Trajectories, within-program variation, and where suppression limits what we can see. 900+ institutions, 33 states, three credential levels.
A bachelor's in child development earns about the same as a sub-associate certificate. PSEO earnings for Human Development and Family Studies graduates, paired with BLS OEWS wages and MIT Living Wage data across states.
View analysis →Do bachelor's degrees from community colleges deliver comparable labor market value? Using Census Bureau earnings data at 1, 5, and 10 years post-graduation, CCB graduates match or exceed traditional BA earnings in most fields by Year 5.
View analysis →How the AI Exposure Index is constructed: variable selection from O*NET, dimension scoring for digital intensity, human interaction shield, and physical anchor, and the crosswalk from occupations to academic programs.
Read methodology →Data sources, formula, population filters, cohort pooling rationale, and the five key approximations behind the Value-Added Earnings Test tool.
Read methodology →What the Post-Secondary Employment Outcomes data can and can't tell us about program value. UI coverage gaps, small-cell suppression, and non-random missingness, layered out.
Read methodology →"Community colleges aren't just sitting in a safe harbor. They're absorbing the students trying to get out of the weather."
Read article →"When Workforce Pell passed as part of the One Big Beautiful Bill Act, the policy conversation immediately turned to one question: will our programs pass the earnings test? The value-added earnings test is not the obstacle most people think it is."
Read article →Institutions use this data to benchmark programs, shape strategy, and respond to accountability requirements. If you need custom analysis for your state, system, or college, want to collaborate on research, or have a question about the methodology, send a message.