Artificial Intelligence, Task Automation and Macro-development: Modelling the productivity- welfare trade offs in the Nigeria Economy

This paper focuses on analyzing the implications of adopting generative artificial intelligence (AI) at the macroeconomic level in Nigeria through a task-based method of analysis informed by Acemoglu in 2018. In breaking the production process into individual tasks that are carried out either by labor or capital, the study then examines the impact of automation and task complementarities resulting due to AI, on productivity, gross domestic product (GDP), wages, and inequality due to a 10-year time frame. Based on the empirical estimates recorded by some related literatures regarding the effects of capital stock on the total factor productivity (TFP) of three economies, the paper is likely to improve by 0.51% to 0.66% depending on the growth of the capital stock; this translates to an increment in GDP of about 0.93 to 1.16 per cent. Every 10,000 when capital investment is higher by an upper scenario, GDP will increase by up to 1.56 percent. Nonetheless, the welfare issues arise due to the occurrence of bad jobs like misinformation and digital manipulation, which may have the potential to negate up to 0.072 percent gain in the GDP. Demographic and education-based impacts differ as the workers with low educational skills have a slight advantage, whereas those with high skills remain unaffected. Income share held by capital also will increase boosting inequality. The paper highlights the importance of focus on inclusive AI approaches, ethical governance and investments in digital infrastructure in Nigeria. Generative AI is promising in its economic development but will depend on the institutional decisions on its usage, their regulatory rules, and deliberate integration with national development plans.