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Cited by 172Artificial Intelligence ApplicationsEthics and Social Impacts of AIInternet of Things and AI

Artificial intelligence in developing countries: bridging the gap between potential and implementation

Open access
Adebayo Olusegun Aderibigbe, Peter Efosa Ohenhen, Nwabueze Kelvin Nwaobia, Joachim Osheyor Gidiagba, Emmanuel Chigozie Ani·2023·Computer Science & IT Research Journal
DOI 10.51594/csitrj.v4i3.629
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Abstract

This paper examines the role of Artificial Intelligence (AI) in developing countries, focusing on bridging the gap between its vast potential and effective implementation. As AI technologies advance globally, their impact on socio-economic development becomes increasingly critical, particularly in regions with diverse challenges and opportunities. The study investigates the current landscape of AI adoption in developing countries, analyzing the potential benefits, challenges, and ethical considerations. Through a comprehensive review of literature and case studies, the paper explores strategies and solutions for harnessing AI's transformative power in diverse sectors such as healthcare, agriculture, and education. The findings emphasize the importance of capacity building, public-private partnerships, and tailored policy frameworks to address infrastructure limitations and skill gaps. The research contributes to a nuanced understanding of the opportunities and complexities surrounding AI implementation in developing countries, providing insights for policymakers, practitioners, and scholars seeking to navigate this evolving technological landscape Keywords: Artificial Intelligence; Global Connectivity; Emerging Technologies; Organizational Resilience; Sustainable Growth; Developing Country.

AI snapshot

Written from the paper’s full text.

TL;DR

This review examines AI adoption in developing countries, arguing that AI can support economic growth, healthcare, education, agriculture, finance, and governance but faces infrastructure, skills, and ethical barriers. It proposes strategies such as infrastructure investment, capacity building, public-private partnerships, and ethical/regulatory frameworks to bridge potential and implementation.

Key findings

  • AI adoption in developing countries is increasing in sectors such as healthcare, agriculture, education, and governance, while developed countries lead due to stronger infrastructure, R&D investment, skilled workforces, and conducive regulation.
  • Potential benefits include economic growth and job creation, improved healthcare diagnostics and remote monitoring, personalized education, and precision agriculture; the paper cites the McKinsey Global Institute that AI could contribute significantly to global economic output by 2030, without giving a numeric value.
  • Challenges include infrastructure limitations (high-speed internet, computing resources, data storage, power supply), skill gaps and education challenges, and ethical/societal concerns such as algorithmic bias, transparency, privacy, security, job displacement, and inequality.
  • Case studies illustrate implementation: India’s CropIn for precision agriculture, Kenya’s Ilara Health for AI diagnostics, Brazil’s INPE for Amazon deforestation monitoring, Rwanda’s Smart Africa/Zindi for personalized learning, and Vietnam’s NAPAS for AI-driven financial inclusion chatbots. Strategies proposed include capacity building, infrastructure development, public-private partnerships, national AI strategies, incentives, and regulatory frameworks.

Methods

  • The paper is a comprehensive review of literature and case studies, synthesizing existing literature, analyzing pertinent case studies, and scrutinizing real-world examples.
  • No primary data collection, sample, or quantitative analysis is reported; no systematic search protocol or inclusion criteria are described.
  • Case studies from selected developing countries—India, Kenya, Brazil, Rwanda, and Vietnam—are used to illustrate AI implementation.

Limitations

  • The paper does not state explicit limitations.
  • Evident from the text: it is a narrative review without a described systematic search strategy, inclusion criteria, or critical appraisal, so the selection and synthesis may be non-exhaustive.
  • Evident from the text: the case studies are brief and descriptive, with no outcome metrics or evaluation data, and claims about benefits rely on cited secondary sources.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.51594/csitrj.v4i3.629

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 36 cited sources checked · 0 supported · 0 flagged

  • Premisenone given

    Economic, infrastructural, and educational disparities create hurdles that impact the equitable distribution of AI benefits in developing countries.

    “Economic, infrastructural, and educational disparities create hurdles that impact the equitable distribution of AI benefits.”
    Quote in the paperSubstantial claim
  • Premisenone given

    AI is being deployed in diverse sectors such as healthcare, agriculture, education, and governance in developing countries to unlock efficiencies and drive innovation.

    “Notably, AI is being deployed in diverse sectors such as healthcare, agriculture, education, and governance to unlock efficiencies and drive innovation.”
    Quote in the paperNot a substantial claim
  • Interpretationreasoning

    As AI adoption proliferates, the creation of new markets, products, and services will stimulate economic activity.

    “As AI adoption proliferates, it is anticipated that the creation of new markets, products, and services will stimulate economic activity.”
    Quote in the paperSubstantial claim
  • Premisecitation

    AI applications assist in automating administrative tasks, allowing educators to focus on interactive and personalized teaching methods.

    “AI applications also assist in automating administrative tasks, allowing educators to focus on interactive and personalized teaching methods (UNESCO, 2019)”
    • Also stated in: § The Role of AI in Specific Sectors · plain
      “Furthermore, AI facilitates administrative tasks, freeing up educators to focus on innovative teaching methods (UNESCO, 2019).”
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    • cites UNESCO, 2019

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  • Premisecitation

    The adoption and integration of AI present a distinctive set of challenges and opportunities for developing countries.

    “While the transformative potential of AI is evident, its adoption and integration present a distinctive set of challenges and opportunities for developing countries (Sood, Sharma, and Bhardwaj, 2022;Biswas, 2020).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Sood, Sharma, and Bhardwaj, 2022

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    • cites Biswas, 2020

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  • Classified as probably not a substantial claim. 39
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  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationnone given

    AI has the potential to drive innovation, improve public services, and address pressing issues in healthcare, agriculture, and education in developing countries.

    “AI has the potential to drive innovation, improve public services, and address pressing issues in healthcare, agriculture, and education in developing countries.”
    Quote in the paperNot a substantial claim

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    Premisecitation

    AI has emerged as a transformative force globally, reshaping industries, societies, and how individuals interact with information.

    “The global ascent of Artificial Intelligence (AI) stands as one of the most transformative phenomena in contemporary technological landscapes, reshaping the way societies operate, businesses function, and individuals interact with information (Mannuru et al., 2023).”
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    Developing countries have increasingly embraced AI technologies in recent years, recognizing their potential to catalyze economic growth, enhance public services, and address societal challenges.

    “In recent years, developing countries have increasingly embraced AI technologies, recognizing their potential to catalyze economic growth, enhance public services, and address pressing societal challenges.”
    Quote in the paperNot a substantial claim

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    Premisecitation

    The creation of jobs in AI development, maintenance, and oversight contributes to the growth of a skilled workforce and fosters entrepreneurship in emerging technological fields.

    “The creation of jobs in AI development, maintenance, and oversight becomes essential, contributing to the growth of a skilled workforce and fostering entrepreneurship in emerging technological fields (Arntz et al., 2016)”
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    • cites Arntz et al., 2016

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    Premisereasoning

    The digital divide exacerbates disparities and limits widespread adoption of AI solutions in developing countries.

    “The digital divide, reflective of uneven access to technology, exacerbates these disparities and limits the widespread adoption of AI solutions.”
    Quote in the paperSubstantial claim

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    Premisenone given

    The trajectories of AI adoption in developed nations have been shaped by significant investments in R&D, a highly skilled workforce, and a conducive regulatory environment.

    “The trajectories of AI adoption in developed nations have been shaped by significant investments in research and development, a highly skilled workforce, and a conducive regulatory environment.”
    Quote in the paperNot a substantial claim

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    Premisecitation

    AI applications in crop monitoring, pest control, and predictive analytics contribute to sustainable agricultural practices, ensuring food security and bolstering farmers' livelihoods.

    “AI applications in crop monitoring, pest control, and predictive analytics contribute to sustainable agricultural practices, ensuring food security and bolstering the livelihoods of farmers (FAO, 2020)”
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    • cites FAO, 2020

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  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisenone given

    AI adoption in developing nations is driven by technological advancements, increased connectivity, and growing awareness of AI's transformative power.

    “The adoption of AI in developing nations is driven by a confluence of factors, including technological advancements, increased connectivity, and a growing awareness of the transformative power of AI applications.”
    Quote in the paperNot a substantial claim

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    Premisereasoning

    Developed countries have been at the forefront of AI development and implementation due to robust technological infrastructures and well-established innovation ecosystems.

    “Developed countries, often characterized by robust technological infrastructures and well-established innovation ecosystems, have been at the forefront of AI development and implementation.”
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    Premisenone given

    Ethical considerations such as bias in algorithms and responsible AI use add complexity to AI integration.

    “Ethical considerations, such as bias in algorithms and responsible AI use, add complexity to the integration process.”
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    Premisecitation

    AI has evolved from a niche field to a pervasive force driving innovation across diverse sectors.

    “Artificial Intelligence, characterized by machine learning algorithms, neural networks, and advanced computing capabilities, has evolved from a niche field to a pervasive force driving innovation across diverse sectors (Gupta et al., 2021, Zhang et al., 2021, Ukoba and Jen, 2022, Sanni et al., 2024).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Gupta et al., 2021

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    • cites Zhang et al., 2021

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    • cites Ukoba and Jen, 2022

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    Premisenone given

    AI has become an integral part of industries such as healthcare, finance, manufacturing, and beyond.

    “From voice-activated personal assistants to complex predictive analytics, AI has become an integral part of industries such as healthcare, finance, manufacturing, and beyond.”
    Quote in the paperNot a substantial claim

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    Premisenone given

    Personalized learning platforms powered by AI can adapt to individual student needs, overcoming resource constraints and fostering inclusive education.

    “Personalized learning platforms powered by AI can adapt to individual student needs, overcoming resource constraints and fostering inclusive education.”
    Quote in the paperNot a substantial claim

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    Premisenone given

    Automation driven by AI can enhance productivity across industries, leading to increased efficiency and competitiveness.

    “Automation, driven by AI, can enhance productivity across industries, leading to increased efficiency and competitiveness.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    AI technologies could contribute significantly to global economic output by 2030, with developing countries poised to benefit from this growth.

    “A study by the McKinsey Global Institute indicates that AI technologies could contribute significantly to global economic output by 2030, with developing countries poised to benefit from this growth (Manyika et al., 2017)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Manyika et al., 2017

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  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Premisenone given

    Developed countries have witnessed extensive integration of AI across industries, from advanced robotics in manufacturing to sophisticated AI algorithms in finance and business analytics.

    “Developed countries have witnessed extensive integration of AI across industries, with applications ranging from advanced robotics in manufacturing to sophisticated AI algorithms in finance and business analytics.”
    Quote in the paperNot a substantial claim

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    Premisenone given

    Education systems are incorporating AI for personalized learning experiences, and governments are exploring AI applications for public service delivery and policy formulation.

    “Education systems are incorporating AI for personalized learning experiences, and governments are exploring AI applications for public service delivery and policy formulation.”
    Quote in the paperNot a substantial claim

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    Premisenone given

    Precision agriculture enabled by AI optimizes resource use, enhances crop yields, and mitigates environmental impact.

    “In agriculture, AI-driven precision farming is optimizing resource use and improving yields.”
    • Also stated in: § Potential Benefits of AI in Developing Contexts · plain
      “Precision agriculture, enabled by AI, optimizes resource use, enhances crop yields, and mitigates environmental impact.”
    Quote in the paperNot a substantial claim

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    Premisecitation

    AI-driven technologies generate new opportunities that require human expertise, even as some routine and manual tasks become automated.

    “While some routine and manual tasks may become automated, AI-driven technologies generate new opportunities that require human expertise.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationnone given

    The gap in AI implementation in developing countries can be bridged through strategic and concerted efforts.

    “The gap in AI implementation, particularly in developing countries, can be bridged through strategic and concerted efforts.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The proposed strategies (capacity building, infrastructure development, public-private partnerships) are effective in bridging the AI implementation gap in developing countries.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Premisenone given

    INPE utilizes AI algorithms to analyze satellite imagery and monitor deforestation in real-time.

    “The Instituto Nacional de Pesquisas Espaciais (INPE) utilizes AI algorithms to analyze satellite imagery and monitor deforestation in real-time.”
    Quote in the paperNot a substantial claim

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    Premisecitation

    AI-driven algorithms optimize trading strategies, improving efficiency and market outcomes.

    “AI-driven algorithms also optimize trading strategies, improving efficiency and market outcomes (Wang et al., 2020).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Wang et al., 2020

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    Premisenone given

    Bias in algorithms, lack of transparency in decision-making, and concerns about data privacy and security are paramount ethical considerations in AI implementation.

    “Bias in algorithms, a lack of transparency in decision-making processes, and concerns about data privacy and security are paramount ethical considerations.”
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    Premisecitation

    AI plays a pivotal role in risk management, fraud detection, and customer service in the finance sector.

    “In the finance sector, AI plays a pivotal role in risk management, fraud detection, and customer service.”
    Quote in the paperNot a substantial claim

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    Premisenone given

    The Smart Africa initiative collaborates with companies like Zindi Africa to implement AI-driven platforms that provide personalized learning content.

    “The Smart Africa initiative collaborates with companies like Zindi Africa to implement AI-driven platforms that provide personalized learning content.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationreasoning

    Developing countries can benefit from partnerships with tech companies, research institutions, and international organizations.

    “Developing countries can benefit from partnerships with tech companies, research institutions, and international organizations.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The proposed strategies (capacity building, infrastructure development, public-private partnerships) are effective in bridging the AI implementation gap in developing countries.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    Localized research efforts ensure that AI solutions are tailored to the specific needs and challenges of developing countries.

    “Localized research efforts ensure that AI solutions are tailored to the specific needs and challenges of developing countries.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The proposed strategies (capacity building, infrastructure development, public-private partnerships) are effective in bridging the AI implementation gap in developing countries.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning

    AI in education in Rwanda aims to bridge educational gaps and improve learning outcomes.

    “AI in education in Rwanda aims to bridge educational gaps and improve learning outcomes.”
    Quote in the paperNot a substantial claim

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    Premisecitation

    AI algorithms analyze production data to enhance product quality and adapt manufacturing processes in real-time.

    “AI algorithms analyze production data to enhance product quality and adapt manufacturing processes in real-time (Lee et al., 2019)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
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    Premisenone given

    Social acceptance of AI is crucial for its successful implementation.

    “The social acceptance of AI is crucial for its successful implementation.”
    Quote in the paperNot a substantial claim

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    Interpretationreasoning

    This AI-driven approach optimizes resource use, improves yields, and contributes to sustainable agriculture.

    “This AI-driven approach optimizes resource use, improves yields, and contributes to sustainable agriculture”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationnone given

    Accessible and robust infrastructure forms the foundation for effective AI implementation.

    “Accessible and robust infrastructure forms the foundation for effective AI implementation.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The proposed strategies (capacity building, infrastructure development, public-private partnerships) are effective in bridging the AI implementation gap in developing countries.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisenone given

    Brazil is deploying AI to address environmental challenges, particularly in the Amazon rainforest.

    “Brazil is deploying AI to address environmental challenges, particularly in the Amazon rainforest.”
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    Premisenone given

    Ilara Health utilizes AI-driven diagnostic tools to enhance medical imaging analysis.

    “The company Ilara Health utilizes AI-driven diagnostic tools to enhance medical imaging analysis.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Interpretationreasoning

    The key strategy for bridging the AI gap includes capacity building, infrastructure development, and public-private partnerships.

    “The key strategy for bridging AI gap includes capacity building, infrastructure development, public-Private Partnerships as shown in the figure 2.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The proposed strategies (capacity building, infrastructure development, public-private partnerships) are effective in bridging the AI implementation gap in developing countries.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given

    AI implementation introduces ethical challenges that necessitate thoughtful strategies to ensure fairness, address bias, and uphold privacy and security.

    “Artificial Intelligence (AI) implementation introduces ethical challenges that necessitate thoughtful strategies to ensure fairness, address bias, and uphold privacy and security.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: AI technologies can be deployed in developing countries in a way that ensures fairness, privacy, and security and benefits all segments of society.

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning

    Knowledge exchange, joint research projects, and sharing best practices contribute to a collective effort in bridging the AI gap.

    “Knowledge exchange, joint research projects, and sharing best practices contribute to a collective effort in bridging the AI gap.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The proposed strategies (capacity building, infrastructure development, public-private partnerships) are effective in bridging the AI implementation gap in developing countries.

  • May combine two claims.

    Interpretationreasoning

    These chatbots enable secure and convenient financial transactions, fostering financial inclusion in regions with limited banking infrastructure.

    “These chatbots enable secure and convenient financial transactions, fostering financial inclusion in regions with limited banking infrastructure.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    This AI-driven approach helps authorities detect illegal logging and enforce environmental regulations.

    “This AI-driven approach helps authorities detect illegal logging and enforce environmental regulations.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Premisenone given

    Ilara Health's portable diagnostics facilitate healthcare delivery in remote areas, addressing challenges of distance and limited medical infrastructure.

    “Ilara Health's portable diagnostics also facilitate healthcare delivery in remote areas, addressing the challenges of distance and limited medical infrastructure.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    In the retail sector, AI applications include demand forecasting, personalized marketing, and inventory management.

    “In the retail sector, AI applications include demand forecasting, personalized marketing, and inventory management.”
    Quote in the paperNot a substantial claim

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    Premisenone given

    AI applications in education include personalized learning platforms, intelligent tutoring systems, and automated grading systems.

    “AI applications in education include personalized learning platforms, intelligent tutoring systems, and automated grading systems.”
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  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    Public-private partnerships can facilitate the sharing of resources, expertise, and data.

    “Public-private partnerships can facilitate the sharing of resources, expertise, and data.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The proposed strategies (capacity building, infrastructure development, public-private partnerships) are effective in bridging the AI implementation gap in developing countries.

  • May combine two claims.

    Premisecitation

    AI transforms manufacturing processes through predictive maintenance, quality control, and supply chain optimization.

    “AI transforms manufacturing processes through predictive maintenance, quality control, and supply chain optimization.”
    Quote in the paperNot a substantial claim

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    Premisecitation

    Predictive analytics optimizes pricing strategies and inventory levels, reducing costs and enhancing profitability.

    “Predictive analytics optimizes pricing strategies and inventory levels, reducing costs and enhancing profitability (Verhoef et al., 2020)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Verhoef et al., 2020

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    Premisecitation

    Ensuring ethical AI practices safeguards against potential misuse and supports the responsible and beneficial deployment of AI technologies in developing countries.

    “Ensuring ethical AI practices safeguards against potential misuse and supports the responsible and beneficial deployment of AI technologies in developing countries (Floridi et al., 2021, Murphy and Barr, 2022, Shneiderman, 2020)”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Floridi et al., 2021

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    • cites Murphy and Barr, 2022

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    • cites Shneiderman, 2020

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    • Rests on an assumption: AI technologies can be deployed in developing countries in a way that ensures fairness, privacy, and security and benefits all segments of society.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Fostering diversity within AI development teams and engaging with stakeholders in the decision-making process helps identify and rectify biases, ensuring that AI applications are fair and equitable.

    “Additionally, fostering diversity within AI development teams and engaging with stakeholders in the decision-making process helps identify and rectify biases, ensuring that AI applications are fair and equitable (Suresh, and Guttag, 2019)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Suresh, and Guttag, 2019

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  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    The challenges and opportunities of AI in developing countries extend beyond national borders.

    “The challenges and opportunities of AI in developing countries extend beyond national borders.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationnone given

    Developing countries face challenges in infrastructure, skills, and ethical considerations, yet within these challenges lie opportunities for leapfrogging traditional constraints.

    “Developing countries face challenges in infrastructure, skills, and ethical considerations, yet within these challenges lie opportunities for leapfrogging traditional constraints.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given

    AI is making significant impacts across sectors, from improving healthcare delivery and educational outcomes to optimizing agricultural practices and transforming financial services.

    “AI is making significant impacts across sectors, from improving healthcare delivery and educational outcomes to optimizing agricultural practices and transforming financial services.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning

    The multifaceted applications of AI underscore its versatility in addressing diverse challenges.

    “The multifaceted applications of AI underscore its versatility in addressing diverse challenges.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationnone given

    Precision applications tailored to local needs, coupled with strategic policies, can ensure that the benefits of AI are distributed equitably, contributing to sustainable and inclusive development.

    “Precision applications tailored to local needs, coupled with strategic policies, can ensure that the benefits of AI are distributed equitably, contributing to sustainable and inclusive development.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The proposed strategies (capacity building, infrastructure development, public-private partnerships) are effective in bridging the AI implementation gap in developing countries.
    • Rests on an assumption: AI technologies can be deployed in developing countries in a way that ensures fairness, privacy, and security and benefits all segments of society.
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  • The paper relies on this without support.

    The proposed strategies (capacity building, infrastructure development, public-private partnerships) are effective in bridging the AI implementation gap in developing countries.

    “The key strategy for bridging AI gap includes capacity building, infrastructure development, public-Private Partnerships as shown in the figure 2.”
    “By employing these strategies, stakeholders can work collaboratively to bridge the gap in AI implementation.”

  • The paper relies on this without support.

    AI technologies can be deployed in developing countries in a way that ensures fairness, privacy, and security and benefits all segments of society.

    “Ensuring ethical AI practices safeguards against potential misuse and supports the responsible and beneficial deployment of AI technologies in developing countries (Floridi et al., 2021, Murphy and Barr, 2022, Shneiderman, 2020)”
    “The goal is to create an environment where AI technologies contribute to inclusive development, ensuring that the benefits of these innovations reach all segments of society in developing countries.”
2 of 2

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The deployment of AI-powered chatbots and virtual assistants ensures continuous and responsive customer engagement, reducing service bottlenecks and operational costs.

    “The deployment of AI-powered chatbots and virtual assistants ensures continuous and responsive customer engagement, reducing service bottlenecks and operational costs (Aderibigbe et al., 2023).”

    From Artificial Intelligence Adoption for Sustainable Development in SMEs: Challenges, Strategic Pathways, and Lessons for Developing Economies (2026) · cites this paper as Aderibigbe et al., 2023

    In “The Role of AI in Specific Sectors” (page unavailable), the paper says chatbots and virtual assistants enhance customer interactions. It does not say they ensure continuous engagement or reduce service bottlenecks or operational costs; the retail passage attributes cost reductions to predictive analytics instead. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • A comprehensive and integrated analysis of AI adoption in SMEs in developing economies is underexplored.

    “Existing research often broadly discusses AI readiness or national strategies (Aderibigbe et al., 2023) and identifies common challenges (Shonhe & Kolobe, 2023), but a comprehensive and integrated analysis is notably underexplored.”

    From Artificial Intelligence Adoption for Sustainable Development in SMEs: Challenges, Strategic Pathways, and Lessons for Developing Economies (2026) · cites this paper as Aderibigbe et al., 2023

  • Without culturally congruent adaptation, AI risks becoming a tool that widens rather than bridges healthcare inequalities.

    “Without culturally congruent adaptation, AI risks becoming a tool that widens rather than bridges healthcare inequalities (21, 22).”

    From Artificial intelligence in nursing: an integrative review of clinical and operational impacts (2025) · cites this paper as [21]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Suresh and Guttag citation year conflicts with reference list

    Minor

    The text cites Suresh and Guttag as a 2019 publication, but the corresponding reference lists 2021.

1 of 1

Cites

Flagged first, then by citations

2 of the 32 references couldn’t be matched to a known paper.

Research works printed but not linked: 4

  1. Lee, L. H., & Ramesh, S. (2019). Artificial intelligence in manufacturing: A review. Journal of Manufacturing Systems, 53, 261-270.
  2. Rana, M.M. (2023). Conservation Agriculture for Sustainable Crop Productivity and Economic Return for the Smallholders of Bangladesh: A Systematic Review. Turkish Journal of Agriculture-Food Science and Technology, 11(10), 2009-2015.
  3. Shaktawat, P., & Swaymprava, S. (2024). Digital Agriculture: Exploring the Role of Information and Communication Technology for Sustainable Development. Ed. Biswajit Mallick and Jyotishree Anshuman published by PMW, New Delhi, p.31. Shneiderman, B. (2020). Bridging the gap between ethics and practice: guidelines for reliable, safe, and trustworthy human-centered AI systems. ACM Transactions on Interactive Intelligent Systems (TiiS), 10(4), 1-31.
  4. Verhoef, P. C., Kannan, P. K., & Inman, J. J. (2020). From Multi-Channel Retailing to Omni- Channel Retailing: Introduction to the Special Issue on Multi-Channel Retailing. Journal of Retailing, 96(1), 1-6.

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Authors
Aderibigbe, A. O., Ohenhen, P. E., Nwaobia, N. K., Gidiagba, J. O., & Ani, E. C.
Affiliations
  • University of Nebraska–Lincoln (US)
  • University of Johannesburg (ZA)
ORCID
Joachim Osheyor Gidiagba
Venue
Computer Science & IT Research Journal
Publisher
Fair East Publishers
Published
2023-12-03
Volume
4
Issue
3
Pages
185-199
ISSN
  • 2709-0043 (ISSN-L)
  • 2709-0051
DOI
10.51594/csitrj.v4i3.629
OpenAlex
W4389286730
Semantic Scholar
3d7d961a9278d53f004238e83715d66be6fb1b23
Cited by
172
References
32
Citations by year
2026: 62 · 2025: 77 · 2024: 33
FWCI
15.22
Type
journal article
Language
en
Open access
Licence
Locations
Computer Science & IT Research Journal (publishedVersion, cc-by-nc)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
Keywords
artificial intelligence adoption, developing countries, socio-economic development, AI ethics, health care, capacity building, public-private partnerships, AI policy frameworks, digital infrastructure, skills gap

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