Ramazan Yener, University of Illinois Urbana–Champaign
Organizations across sectors hire many privacy professionals. Yet we have limited empirical evidence about how privacy roles are defined in hiring practices. This talk presents insights from an ongoing analysis of privacy-related job postings across major hiring platforms. The research uses a multi-stage approach that includes Natural Language Processing (NLP) to examine how employers describe privacy responsibilities, what kinds of skills and backgrounds they seek, and how often privacy work is connected to AI and emerging technologies. At a high level, privacy roles are increasingly hybrid, combining legal, technical, and organizational responsibilities. Results show growing signals that privacy teams are being positioned as part of broader AI governance and risk management efforts. These findings provide a practical snapshot of how privacy work is evolving and raise important questions about workforce development, training, and team design.
Researchers: Ramazan Yener, Muhammad Hassan, Masooda Bashir
Ramazan Yener is an academic researcher at the iSPICE Lab and a PhD student in Information Science at the University of Illinois Urbana–Champaign, focusing on privacy engineering, AI governance, and cybersecurity. His research examines how privacy is operationalized in practice, including studies of privacy engineering roles, national and international standards (ISO/IEC 27001, ISO/IEC 27701, NIST AI RMF, NIST CSF, and the NIST Privacy Framework), and the privacy risks of AI-driven systems such as healthcare chatbots, agentic AI, and IoT-enabled platforms. He approaches these systems from a user-centered and socio-technical perspective to identify where design and governance choices introduce privacy and security risks.
author = {Ramazan Yener},
title = {Mapping the Privacy Workforce in the {AI} Era},
year = {2026},
address = {Santa Clara, CA},
publisher = {USENIX Association},
month = jun
}