Introduction
The Fourth Industrial Revolution is reshaping work at pace, yet the career competencies required to navigate this transformation remain poorly understood, particularly in contexts marked by structural inequality and limited digital infrastructure. South Africa, with an unemployment rate of 32.7% and persistent skills mismatches, cannot rely on frameworks developed for conditions fundamentally different from its own. Critically, no validated, context-specific career competency framework currently exists for the South African formal professional sector engaged in 4IR-related career development an empirical, methodological, and contextual gap this study directly addresses.
Methods
A two-round modified Delphi technique was employed with a purposively selected panel of South African experts drawn from industrial psychology, human resource management, organizational learning, and education across multiple provinces and sectors. Round 1 assessed definitional clarity of 38 candidate competencies derived from prior qualitative interviews, resulting in 23 retained, 12 refined, and five removed, with 35 competencies proceeding to Round 2. Round 2 applied dual thresholds for definitional precision and strategic importance across all 35 competencies.
Results
Twenty-six competencies met all retention criteria and were organized into two tiers: 12 critical core competencies and 14 important contributors. The four highest-ranked competencies were career adaptability, ethical behavior, digital literacy, and continuous learning. Notably, three technology-related competencies, including artificial intelligence and digital agility, were excluded despite high importance ratings owing to insufficient definitional clarity, illustrating that perceived relevance cannot substitute for operational precision.
Discussion
To the best of the authors' knowledge, this study presents the first expert-validated 4IR career competency framework developed specifically for the South African formal professional sector, addressing a significant empirical, methodological, and contextual gap in the career development literature. For curriculum designers and educators preparing graduates for AI-integrated workplaces, the framework offers both a validated set of teachable competencies and a concrete illustration of why AI-related skills resist easy formalization, a finding with direct implications for programme design and sequencing. The framework provides career psychologists with assessment-ready competency definitions, offers HR practitioners a sequenced developmental roadmap, and gives educators and policymakers an empirically grounded basis for curriculum alignment and skills policy reform, whilst demonstrating partial convergence with international workforce priorities.