Scaled for Whom? Equity, AI Career Tools, and the Students They Leave Behind

Institutions are deploying AI-powered career platforms faster than ever, promising personalized guidance, increased access, and better student outcomes. But for first-generation students, students of Color, and other underrepresented groups, these tools often deliver something else: exclusion and "resources" that do not meet their needs. Most career technology was built on a default professional whose identity, networks, and cultural capital already align with dominant workplace norms. When AI scales that default, it doesn't democratize opportunity—it perpetuates inequity. This session challenges higher education professionals to examine what and for whom we're really building when we invest in AI career tools. Drawing on practitioner experience in career development, research on school-to-work transitions and belonging, and the development of identity-centered career resources, this session offers a critical framework for evaluating the tools we implement and the assumptions baked into them. Attendees will leave with concrete language and criteria for auditing career technology through an equity lens; strategies for advocating within their institutions for more identity-centered approaches; and a reframe of student success that centers belonging alongside outcomes data. This session is for career center professionals, student success personnel, and higher education leaders who are committed to championing career equity.