AI can boost growth in BRICS but worsen poverty without strong governance

The findings show that while AI adoption is statistically linked to increases in GDP per capita, it also correlates with rising poverty in countries with fragile institutions. The study warns that unless governance is strengthened, the benefits of AI could be unequally distributed, potentially worsening income inequality and social exclusion.

Artificial intelligence (AI) can promote long-term economic growth in BRICS-Plus countries but may simultaneously increase poverty in the short term if governance frameworks are weak, a new international study has found.

Published in the journal AI & Society, the study "Artificial intelligence (AI)-poverty-economic growth nexus in selected BRICS-Plus countries: does the moderating role of governance matter?" by Dr. Charles Shaaba Saba of the University of Johannesburg analyzed data from 2012 to 2023 across Brazil, Russia, India, China, and South Africa. Using econometric modeling, the research assessed whether AI investments contribute to higher GDP and reduced poverty, and whether governance quality influences these outcomes.

The findings show that while AI adoption is statistically linked to increases in GDP per capita, it also correlates with rising poverty in countries with fragile institutions. The study warns that unless governance is strengthened, the benefits of AI could be unequally distributed, potentially worsening income inequality and social exclusion.

AI linked with higher growth, but short-term poverty spike

The research found that a 1% increase in AI investment is associated with a 0.016% rise in GDP per capita among the BRICS nations. However, in the short term, AI adoption contributed to higher poverty rates, particularly in countries with weak labor markets or limited digital access.

According to the study, AI’s economic efficiency gains can lead to job displacement and wage polarization in the early phases of deployment, effects that disproportionately impact lower-income households. The lack of adequate social safety nets or retraining programs can cause poverty levels to rise even as overall GDP increases.

A key finding of the study is the moderating role of governance in the AI–poverty–growth nexus. Countries with stronger governance indicators, including regulatory quality, rule of law, and control of corruption, were better able to translate AI-driven growth into poverty reduction.

Using the Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) model, the study showed that good governance amplifies AI’s positive effects on economic performance while minimizing its adverse social impacts.

In contrast, poor governance appeared to neutralize AI’s growth potential and worsen inequality. The presence of weak institutions, political instability, or ineffective public sector management was correlated with rising poverty alongside increased AI deployment.

BRICS countries show diverging trends

While grouped as an emerging economies bloc, the five BRICS nations display divergent patterns in AI readiness and governance strength. China has made the most significant AI investments, while India has prioritized digital inclusion and innovation policy. Brazil and South Africa, despite democratic institutions, struggle with regulatory enforcement and infrastructure gaps. Russia’s governance profile, characterized by centralization and political risk, presented unique challenges.

These variations influence how each country’s AI strategy plays out on the ground. In nations with stronger economic governance, including public financial management and regulatory frameworks, AI was more likely to support poverty alleviation. In others, technological advancements benefited elite sectors with limited trickle-down effects.

The study also conducted panel causality tests, finding that economic growth leads to AI adoption, not vice versa. Additionally, AI was shown to influence governance quality over time, potentially by improving administrative efficiency and data-driven decision-making in the public sector.

This bidirectional link reinforces the need for synchronized progress across institutional and technological domains. “Governments must invest not just in AI capacity, but in the rule of law, anti-corruption enforcement, and regulatory competence,” Saba said.

Policy implications: Technology requires institutions

The study calls for a dual-track approach to AI development: one that combines investment in technology with governance reform. Key recommendations include:

• Strengthening institutional capacity and anti-corruption frameworks to support fair AI deployment.
• Expanding digital infrastructure and training programs to improve access and reduce skills gaps.
• Designing AI-specific regulatory systems to prevent misuse, bias, and inequality.
• Using AI to enhance delivery of public services, including education, welfare, and justice.

Though focused on BRICS nations, the study’s conclusions have broader implications for the Global South. Many developing economies are turning to AI as part of digital transformation agendas, often without robust institutional checks.

International bodies such as the UNDP and World Bank have highlighted governance as a prerequisite for ethical and equitable AI. The findings from this study reinforce that perspective, offering empirical evidence that AI’s promise hinges on the political systems around it.