The Generative Logic and Evolutionary Pathways of Emerging Occupations in the AIGC Era: An Analytical Framework Based on Technology-Skill-Society Dynamics

Abstract

This study presents a comprehensive theoretical framework to examine how generative artificial intelligence transforms occupational structures through the dynamic interplay of technological capabilities, skill requirements, and societal adaptation. Departing from conventional analyses focused on technical specifications or ethical risks, we develop a novel "technology-skill-society" triad to systematically investigate AIGC's role in occupational evolution. Our analysis reveals three distinct pathways for emerging professions: (1)prompting and optimization-led roles that combine human creative direction with AI execution, (2)evaluation and decision-augmenting positions emphasizing human oversight of AI outputs, and (3)interaction and agent-based occupations redefining human-AI service delivery. Through empirical examination of transformed and newly created occupations across multiple sectors, we identify a hierarchical progression of skill demands—from operational tool proficiency through synergistic workflow integration to strategic innovation capabilities. The findings demonstrate that AIGC drives non-linear occupational transformation characterized by professional boundary erosion, cross-domain skill integration, and the rising premium on uniquely human capacities for ethical judgment, complex problem-framing, and emotional intelligence. We further delineate critical governance challenges in algorithmic accountability, intellectual property regimes, and workforce transition management. The study contributes to labor economics and technology sociology by providing a unified framework to understand occupational metamorphosis in the AI era, offering actionable insights for policymakers, educators, and organizational leaders navigating the human-AI symbiosis.