Business Students Expand Routine AI Use
A survey by American University's Kogod School of Business, conducted from 2024 to 2026, found that routine AI use among business students rose from 6% to 29%. The New York Post reported Aug. 4 that more than 80% had used AI academically in the prior six months, even as graduates booed speakers who discussed AI at 2026 commencements.
American University's Kogod School of Business found routine AI use among surveyed business students rose from 6% to 29% over three years, according to an August 4 New York Post report. The school surveyed 483 business students across 2024, 2025, and 2026. More than 80% reported using AI for academic purposes during the preceding six months, while nearly one-third reported using it at least 11 times weekly for school or work-related tasks.
The reported usage data arrives amid visible student anxiety about AI's labor-market effects. In May, AP reported that University of Arizona graduates repeatedly booed former Google CEO Eric Schmidt after he discussed AI during a commencement address. U.S. News also reported that University of Central Florida graduates booed speaker Gloria Caulfield when she described AI as the "next industrial revolution."
How students report using AI
The New York Post reported that roughly three-quarters of Kogod respondents use AI to brainstorm, 62% use it for summarization, and just over half use it to find information sources. The report also stated that nearly nine in 10 respondents had used Perplexity, 79% named ChatGPT as their preferred model, and 39% cited Anthropic's Claude.
Kogod interim dean Casey Evans told Axios that the school had not encountered substantial resistance and had not required students to use AI without guidance, according to the New York Post.
The survey's figures describe self-reported behavior among business students, not a representative measure of all US college students. Still, separate evidence points in the same direction. Inside Higher Ed reported in April that 85% of surveyed graduating seniors had used AI tools, up 31 percentage points from two years earlier, based on Handshake data from 1,248 students at nearly 500 institutions.
Employment pressure and classroom adoption
The New York Post reported that the share of job interviews containing AI-related questions rose from 12% to 43% across the same three-year period covered by Kogod's survey. Separately, Inside Higher Ed reported that more than 10% of active internships on Handshake mentioned AI-related skills and that 4.2% of full-time postings did so, nearly double the year-earlier share.
For data-science and ML practitioners building educational tools, the reported pattern is important: student adoption is clustering around ideation, summarization, and search-oriented workflows. Comparable technology transitions in education often create a gap between widespread informal use and consistent instruction on source verification, disclosure, and evaluation. The available reporting does not establish how Kogod students validate model outputs, cite AI assistance, or distinguish generated material from reliable sources.
The commencement reactions show that adoption and confidence are not the same measure. AP reported that Schmidt acknowledged graduates' fear during his speech, while Business Insider cited a survey of 14- to 29-year-olds finding declining excitement about AI and rising anger. Together, the reports document a cohort using AI frequently while voicing concern about its consequences for early-career work.
Key Points
- 1Kogod's survey reports routine AI use among business students increased from 6% to 29%, making AI a recurrent academic workflow.
- 2Students reported using AI mainly for brainstorming, summarization, and information discovery, concentrating adoption in knowledge-work tasks.
- 3Comparable education transitions often expose gaps between informal tool adoption and instruction on validation, provenance, disclosure, and responsible use.
Scoring Rationale
The survey provides useful evidence of how generative AI is entering student workflows and early-career preparation. Its limited respondent base and focus on business students constrain generalization, but the findings are relevant to teams building education, productivity, and workforce AI products.
Sources
Public references used for this report.
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