Artificial Intelligence, Task Automation and Macro-Development: Modelling the Productivity – Welfare Trade-Offs in the Nigeria Economy
The study analyses the macroeconomic Implication of the adoption of generative artificial intelligence (AI) in Nigeria via a task-oriented thought framework introduced by Acemoglu & Restrepo (2018). The research time horizon is productively broken down into discrete tasks either by labour or by capital decomposition of production and analyses the impact on total factor productivity (TFP), gross domestic product (GDP), wages, and income distribution over a 10-year horizon due to automation and task complementarities of AI. Using secondary datasets and empirical estimates based on current literature, the paper projects that AI has the capacity of increasing Nigeria TFP by 0.51% to 0.66%, which means that Nigeria GDP will increase by around 0.93% to 1.16%. With more favourable investment expectations GDP benefit could be as large as 1.56%. But the analysis also shows possible welfare losses; up to 0.072% of GDP, due to the bad tasks created by AI (misinformation and other manipulative digital information).
The results in terms of labour markets indicate that there has been a minor wage increase among persons with low education levels but the already well positioned classes have barely been touched. However, it is expected that the share of the income enjoyed by the capital will grow, which will promote inequality in general. These results highlight the need to adopt an inclusive approach to the development of AI solutions in Nigeria, which is to be aided by ethical regulation, strong regulations, and massive investment in digital infrastructure. In as much as generative AI poses valuable ground in economic transformation, its potentials will be realized ultimately through the way institutions orient its inclusion in national development agenda.
© The Author(s) 2025. Published by RITHA Publishing. This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited maintaining attribution to the author(s) and the title of the work, journal citation and URL DOI.
Article’s history: Received 20th of August, 2025; Revised 7th of September, 2025; Accepted for publication 25th of September, 2025; Available online: 30th of September, 2025; Published as article in Volume I, Issue 1(1), 2025.
Ekpeyong, P.G. (2025). Artificial Intelligence, Task Automation and Macro-Development: Modelling the Productivity – Welfare Trade-Offs in the Nigeria Economy. Applied Journal of Economics, Law and Governance, Volume I, Issue 1(1), 89-106. https://doi.org/10.57017/ajelg.v1.i1(1).05
Competing Interests: The author states that there is no competing interest.
Funding: The description and reporting of this research has not been supported by any unique grant raised by any funding institution, whether in the public, commercial, or non-profit-making sectors.
Author(s)' Contributions: The conceptualisation, methodology, data analysis, writing, however, were done solely by the author.
Acknowledgements: The author extends his appreciations to the previous scholar regarding the research that has published their estimate and frameworks publicly and is used in this research. also is acknowledged Dr Noah for his contribution by reviewing the work done.
Data Availability Statement: The data that support the findings of this study were obtained from the World Bank World Development Indicators: https://databank.worldbank.org/source/world-development-indicators, International Labor Organization ILOSTAT database: https://ilostat.ilo.org/ and National Bureau of Statistics, Nigeria: https://nigerianstat.gov.ng/. Additional datasets were drawn from OECD AI Policy Observatory: https://oecd.ai/. Access to these datasets is subject to the terms of use of the respective organizations.
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