Thriving in Uncertainty: The Relationships between Future Job Predictions, Learning Agility, Responsive Attitude, and Adaptability

Abstract

Background: The 2023 World Economic Forum report indicates that the influence of Artificial Intelligence (AI) and automation on the labour sector was more significant than initially anticipated. While a 2018 study predicted substantial employment losses offset by job creation, recent evidence suggests a different outcome.

Objectives: This study aims to identify the principal determinants affecting the adaptability of college graduates in Indonesia. The study equally measures the intensity of the interactions among these variables to comprehend their collective impact on graduate adaptability.

Methodology: The researchers used descriptive survey research in this study, examining 284 Indonesian ICIL policy students who were selected using the purposive sampling technique. A structured questionnaire was used to collect data for the study. This study employed quantitative analysis, using Structural Equation Modeling (SEM) with SmartPLS 4.0.

Results: It was found that job trend forecasting significantly affects responsiveness, with a correlation coefficient of 0.69, while responsiveness strongly influences learning agility, with a coefficient of 0.43. However, there exists no significant direct correlation between job trend forecasts and adaptability (t-value = 0.56).

Conclusion: Adaptability is a multidimensional concept that incorporates job forecasting trend analysis, responsive practices, and learning accelerators. Institutions ought to improve their human resources tactics to better equip graduates for the ever-evolving job market.

Unique Contribution: This study has provided empirical evidence that could guide policies and programmes for preparing graduates for the labour market.