The Role of Artificial Intelligence in Optimizing Poverty Alleviation Programs: A Case Study of NGO Activities in Bauchi State
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- Table of Content: Available
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- NGN 5000
1.1 Background of the Study
Poverty alleviation programs in Bauchi State are essential for improving livelihoods and addressing socio-economic challenges. Non-Governmental Organizations (NGOs) play a critical role in implementing these programs. Artificial Intelligence (AI) has the potential to optimize these efforts by improving resource allocation, predicting program outcomes, and enhancing beneficiary targeting.
AI tools use data analytics, predictive modeling, and decision support systems to identify priority areas, forecast the impact of interventions, and monitor program effectiveness. This ensures that resources are directed toward the most vulnerable populations, maximizing the impact of poverty alleviation programs (Abubakar & Suleiman, 2024). This study examines the role of AI in optimizing NGO-led poverty alleviation efforts in Bauchi State.
1.2 Statement of the Problem
Despite the efforts of NGOs, poverty alleviation programs in Bauchi State often face challenges such as inefficient resource allocation, lack of accurate beneficiary data, and limited impact assessment mechanisms. AI offers solutions, yet its adoption remains low due to technical and operational barriers.
1.3 Objectives of the Study
- To analyze the adoption of AI tools in poverty alleviation programs by NGOs in Bauchi State.
- To evaluate the impact of AI on resource allocation and program outcomes.
- To identify barriers to the implementation of AI in poverty alleviation programs.
1.4 Research Questions
- How are AI tools being used in NGO-led poverty alleviation programs in Bauchi State?
- What is the impact of AI on resource allocation and program outcomes?
- What challenges hinder the adoption of AI in poverty alleviation programs?
1.5 Research Hypothesis
- AI tools significantly improve resource allocation in poverty alleviation programs.
- AI enhances the targeting and impact of poverty alleviation interventions.
- Limited technical capacity and high implementation costs are barriers to AI adoption.
1.6 Significance of the Study
This study provides insights into the potential of AI to optimize poverty alleviation programs, offering recommendations for NGOs and policymakers to enhance program efficiency.
1.7 Scope and Limitations of the Study
The study focuses on NGOs in Bauchi State and their use of AI in poverty alleviation programs. Limitations include variability in program scales and the evolving nature of AI technologies.
1.8 Operational Definition of Terms
- Poverty Alleviation: Efforts aimed at reducing poverty and improving living standards.
- Non-Governmental Organizations (NGOs): Organizations that operate independently of government to address social issues.
- Predictive Modeling: AI techniques used to forecast program outcomes and impacts.
- Resource Allocation: The distribution of financial, material, and human resources for program implementation.
- Beneficiary Targeting: The process of identifying and reaching the most vulnerable populations.
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