Geraint Van Der Rede

The South African labour market’s structural rigidities and extreme inequality present a critical challenge for technological adoption, where the balance between labour-augmenting and labour-displacing effects determines whether productivity gains are shared or lost to rent dissipation (Acemoglu & Restrepo, 2019; 2024). This research investigates these dynamics through three primary pathways: first, by using linked IRP5 employee-tax data to decompose the micro-level impact of industrial automation across age and gender profiles to identify who is retained versus displaced (Kilumelume et al., 2025); second, by building on the conceptual framework of Budlender and Bassier (2025) to evaluate rent-sharing mechanisms and determine if automation-led surpluses are captured as increased wage markdowns under monopsonistic conditions; and third, by applying task-based capability frameworks to forecast whether Generative AI will facilitate task reinstatement or further hollow out the South African skill distribution (Auer et al., 2024; Korinek & Stiglitz, 2017; Felten et al., 2021). Together, these components offer a rigorous evaluation of how successive technological shocks reshape the distributional landscape of the South African labour market.