Rewriting Success: How Generative AI Is Shaping New Definitions of Career Achievement
Abstract
Generative artificial intelligence (GenAI) integration into work life is transforming how earlycareer professionals define and pursue success.This qualitative, phenomenological study investigates how individuals in the early stages of their careers, immersed in AI-enabled environments, construct evolving notions of career success.Using purposive sampling, the study engaged ten participants -five females and five males -who graduated from Academic Year 2022 onwards, represent diverse career fields, and are currently employed or actively seeking work (Patton, 2015).Semi-structured interviews explored their lived experiences, with thematic analysis guided by Career Construction Theory, which views careers as selfconstructed realities through which individuals make sense of their experiences.It emphasizes how people build their careers by using their personal stories, themes, and life experiences to adapt to vocational challenges.This focuses on adaptability, storytelling, and how individuals' personal narratives shape their professional paths, and the Protean Career Model which states that a career path is driven by the individual, not the organization, and that it is guided by a person's intrinsic values and a desire for psychological success, such as personal fulfillment and well-being.Findings reveal that GenAI workplace adoption contributes to a shift from traditional extrinsically oriented markers such as job stability, salary, and title, towards more intrinsic adaptive, and self-directed indicators, like autonomy, continuous learning and ethical AI use, while still preserving creativity and empathy in AI-mediated work.These results affirm protean and boundaryless orientations shaped by technological disruption, indicating the importance of responsive, future-ready career development programs that integrate humancentric values with AI-era competencies.
Fields of Study & Subjects
Artificial Intelligence in Education
Higher Education and Employability
AI and HR Technologies
Publication details
- Journal / source
- Asian Conference on Education official conference proceedings/ACE
- Pages
- 137–159
- Publication date
- 9 February 2026
- Language
- EN