Purpose: This study develops the concept of ghost demography, referring to a demographic condition in which repeated automation-driven disruption gradually produces structurally detached population segments from productive labor market participation. This study aims to explain how technological change, beyond short-term job displacement, may accumulate into long-term socioeconomic exclusion at the population level.

Research Methodology: An exploratory sequential mixed-method design was applied. The qualitative phase involved expert interviews to identify the mechanisms linking automation and exclusion. These insights inform the quantitative phase, which tests the relationships using cross-country labor market and digital economy indicators across 60 country sector observations from international data sets.

Results: The findings reveal three interrelated mechanisms underlying the emergence of ghost demography: economic obsolescence, structural adaptation barriers driven by skill mismatch and digital inequality, and cumulative socioeconomic detachment. Regression analysis indicates that automation exposure significantly increases socioeconomic exclusion. Skill mismatch and digital inequality further intensify this relationship, whereas Institutional Quality moderates the effect by reducing the exclusionary impact of automation.

Conclusions: Automation may progressively reshape labor participation patterns and generate early demographic signatures of exclusion.

Limitations: The analysis relies on aggregated country sector indicators and does not fully capture individual-level labor mobility dynamics.

Contributions: This study contributes to the literature on automation and labor markets by conceptualizing technological exclusion as a demographic transformation process.