The study, “Data Privacy and AI Governance for Marginalized Communities in the United States,” examines the digital divide affecting marginalized groups and its exacerbation by biased AI governance. With the objectives of assessing data privacy risks, analyzing biases in AI systems, and proposing inclusive policies to improve AI governance, the research highlights key findings, including that marginalized communities, particularly racial minorities and low-income populations, face disproportionate risks from surveillance capitalism, biased facial recognition, and AI-driven hiring processes. Healthcare is also affected by the technological bias as AI models less accurately serve marginalized groups owing to unrepresentative data sets. In response, the study recommends stringent data protection laws akin to the European Union’s GDPR, ethical AI standards focused on transparency, as well as mandatory diversity in AI development teams to ensure demographic representation. To address biases in surveillance, the enactment of the George Floyd Justice in Policing Act and the Facial Recognition and Biometric Technology Moratorium Act are recommended. The work concludes with an emphasis on the need for digital inclusion and equitable AI governance to prevent further marginalization and foster fair participation in a digital society.