The study aims to explore the impact of Artificial Intelligence (AI) and human cognitive bias on sustainable skill development in Industry 4.0.
A secondary data analysis is conducted using the Kaggle AI Impact on Job Sector (2026) dataset and the United Nations Educational, Scientific and Cultural Organisation (UNESCO) Science Report (2021). Microsoft Excel is used to perform comparative, pattern, and sectoral workforce analyses.
The data show that even as more organisations adopt AI, disparities persist in workforce participation, representation in leadership positions, and compensation equality. Additional productivity gains are not always accompanied by comparable reward opportunities and continue to vary across sectors and AI-focused career trajectories due to cognitive biases.
The study shifts the focus from whether AI is biased to whether AI-driven organisations provide equitable opportunities to participate, advance, and be recognised. Cognitive Bias Theory (CBT) is used as a novel interpretive theory to explain how organisational asymmetries may persist within data-driven environments.
The study is based on secondary and exploratory data and does not directly measure cognitive bias.
Skills development for sustainable Industry 5.0 requires not just technology but also workforce governance mechanisms that enable and empower inclusive workforce participation, and sustain progression and incentives.
Mester, N. M and Kumar, A. (2026): Artificial intelligence and human cognitive bias in industry 4.0: the need for sustainable skills development. World Journal of Science, Technology and Sustainable Development (WJSTSD), Vol. 21, No. 6, pp. 493-508.
