Explore how the transformative power of Artificial Intelligence can drive socio-economic development in the Global South, addressing critical challenges and unlocking new opportunities.
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By Professor Arthur G.O. Mutambara
A growing body of research has focused on the current Artificial Intelligence (AI) revolution, including its opportunities and threats.
The massive impact on various economic sectors, global Gross Domestic Product (GDP), and employment has been articulated, while the need for enabling governance, legislation, and safety regulations has been emphasised.
However, academic scholarship has focused on the Global North, particularly the United States and Europe.
What about the Global South?
Which countries belong to the Global South?
What is Artificial Intelligence?
How can Artificial Intelligence be used to drive the economies of the Global South?
How can this technological revolution be leveraged to address challenges faced by the least industrialised and emerging economies?
How can AI be utilised to enhance the quality of life for people living in these countries?
Are these economies ready for AI?
How can they prepare and then rapidly adopt AI across all sectors?
More significantly, how can the Global South be a key player in the research, development and production of AI technology, systems, and applications?
What about the hardware required for AI systems - the semiconductor chips that power AI?
Why can't the Global South be involved in this massively lucrative industry?
This intensive and exclusive focus on AI and the Global South has been missing in the literature
This book seeks to close that gap. It is primarily focused on the pivotal role of Artificial Intelligence in driving governance and socio-economic development in the Global South.
Put differently, the book explores how AI can be deployed as a catalyst for inclusive development and shared prosperity in emerging and least industrialised economies.
However, the adoption and harnessing of AI cannot occur in a vacuum.
Forget AI.
Broad (non-AI) interventions must be executed to resolve the perennial challenges bedevilling developing economies:
Poverty, unemployment, inequality, poor governance, corruption, incompetence, democratic deficit, energy poverty, inadequate infrastructure, conflict and insecurity, demographic pressures, global economic imbalances, geopolitical concerns, cultural and social degradation, and limited access to technology and innovation.
A special type of state is required to address these challenges - a capable, ethical, democratic, and developmental state.
Countries in the Global South must transform themselves into such efficacious regimes.
Only within this context will AI be an effective driver of inclusive development and shared prosperity.
The AI-ignited Fourth Industrial Revolution (4IR), which began in 2011, builds upon the Third Industrial Revolution (1965-2011), driven by electronics and information and communication technology (ICT).
Artificial Intelligence is the DNA of the 4IR.
Most countries in the Global South did not substantially benefit from the first three industrial revolutions.
There was slavery from 1619 to 1865, while colonialism characterised most of the emerging and least industrialised African economies from 1884 to 1994.
Even in the so-called post-colonial era, neocolonialism and imperialism continue to ravage and plague the Global South.
Ostensibly, citizens of emerging and least industrialised countries have been objects and victims of the first three technological revolutions.
The AI-ignited 4IR presents a unique opportunity for the Global South to have agency, become critical players and use technology to achieve inclusive development and shared prosperity.
Yes, it might be considered overly ambitious to prescribe the application of AI to such a broad spectrum of countries with varied cultures, development experiences, economic structures, and demographics.
However, the opportunity to share best practices and emergent experiences among these countries and the centrality of South-South cooperation, integration, and scale have a clear and unquestionable value proposition.
Indeed, Artificial Intelligence can be harnessed as a catalyst for economic growth and industrialisation in emerging and least industrialised countries.
The technology has the potential to significantly impact these economies in various domains, bringing both opportunities and challenges.
AI systems can drive economic growth by enhancing productivity, efficiency, and innovation.
The Global South can leverage AI in all industries, including agriculture, mining, manufacturing, banking and finance, tourism and hospitality, education, and healthcare, to boost economic development.
A flurry of bold announcements on AI and its infrastructure in January 2025 from leaders in the Global North, such as UK Prime Minister Keir Starmer, then-US President Joe Biden, and current US President Donald Trump (immediately after his inauguration), signal the urgent and transformative potential of the technology globally.
These highly industrialised economies view AI as a key driver of competitiveness in every sector and are unleashing massive investments in AI research and infrastructure.
China’s release, on January 20, 2025, of a groundbreaking open-source, low-cost, and less energy-intensive Large Language Model called DeepSeek-R1, whose functionality and efficacy are comparable to those of OpenAI’s ChatGPT-4, Google’s Gemini, and xAI’s Grok 3, highlights the immense possibilities for the Global South.
The eloquent message is that:
Yes, people and institutions from emerging and least industrialised economies can develop globally competitive AI systems.
They can be creators of AI, not just users!
It must be conceded and acknowledged that there is quite some heterogeneity in the Global South.
Asian states, such as China, Hong Kong, Singapore, and Malaysia, are far more advanced in terms of policy and governance infrastructure, economic productivity, manufacturing capacity, and, of course, the development and adoption of AI systems, compared to countries in Africa and Latin America.
However, the shared history and similar economic circumstances in the 1950s and 1960s for most countries in the Global South make it imperative that these countries be studied together and lessons are drawn across these economies.
For example, African countries might benefit from understanding how China moved 800 million people out of poverty in 40 years.
Ghana and Singapore had comparable GDPs in 1965 (USD 0.97 billion and USD 1.2 billion, respectively).
Yet, in 2024, the GDP numbers are USD 76 billion and USD 501.4 billion, respectively.
What happened?
Indeed, countries in the Global South can learn from each other.
Hence, their AI opportunities, experiences, challenges and successes must be reviewed together.
AI applications in precision agriculture, crop monitoring, and data-driven decision-making can improve agricultural practices, increase yields, and address food security challenges in the Global South.
AI-driven healthcare solutions, including telemedicine, diagnostic tools, and predictive analytics, can improve healthcare access in regions with a shortage of medical professionals.
Remote monitoring and AI diagnostics can aid in the early detection of diseases.
Furthermore, AI can enhance educational opportunities by providing personalised learning experiences, automating administrative tasks, and expanding access to academic resources.
This is particularly important in areas with limited access to quality education, as with some communities in the Global South.
Many of the banking and financial sectors in the Global South are underdeveloped.
AI-driven fintech solutions can promote financial inclusion by providing access to banking services, credit, and insurance.
Mobile banking, digital wallets, and AI-based credit scoring systems can empower individuals, small businesses, and communities.
Thus, in the Global South, AI applications can empower local communities by addressing specific challenges, such as energy poverty, food security, water management, environmental conservation, and sustainable development.
Community-driven AI projects can be designed and tailored to address local needs.
Additionally, AI can enhance access to information and services in areas with limited infrastructure.
Chatbots, virtual assistants, and AI-driven interfaces can provide information and support, particularly in remote or underserved regions.
In terms of infrastructure development, AI can contribute to the optimisation of infrastructure planning and development.
Smart city initiatives, intelligent transportation systems, and energy-efficient solutions can enhance the overall infrastructure in urban and rural areas.
However, none of these potential AI-driven benefits will automatically accrue to the Global South.
These countries must actively prepare for the adoption of AI and develop effective strategies and mechanisms for its implementation.
An AI ecosystem approach involving the collaboration of governments, businesses, researchers, investors, venture capitalists, and international organisations must be deployed.
Partnerships can facilitate knowledge exchange, technology transfer, and collaborative projects.
More significantly, associations and linkages with the Global North must lead to the Global South becoming producers and owners of AI technology, tools, and systems.
Furthermore, developing countries must also participate in the AI semiconductor industry - the financially lucrative business of producing chips that power AI.
The book discusses the conceptualisation, governance, and economies of the Global South.
Specifically, problems and challenges that characterise these countries are presented and discussed.
The objective is to identify potential redemptive AI interventions in these economies.
The extent to which the Global South participates in knowledge and technology production is explored.
More significantly, the uptake and leverage of technological innovation are evaluated.
The book provides an introduction to Artificial Intelligence within the context of the 4IR, where key drivers of the 4IR are also discussed, and classification, applications, and examples of AI systems are outlined.
The issues of AI safety and the potential dangers of the technology are also discussed.
AI has challenges, risks, and dangers – the Dark Side of Artificial Intelligence.
The book reviews these matters.
In particular, deepfakes, cyberattacks, AI bad actors, autonomous weapons systems (AWS), and autonomous nuclear weapons systems (ANWS) are flagged.
Application and adoption of AI in the Global South are not automatic or guaranteed.
Indeed, participation by emerging and least industrialised economies in producing AI systems and semiconductor chips is not easily accomplished.
The cart must not be put before the horse.There are foundational matters that must be addressed.
These include basic infrastructure, energy and power, funding and investment, digital infrastructure, compute resources, talent and expertise, financial literacy, basic education, and mindset.
The book outlines the necessary measures to ensure the safe and effective adoption of AI in the Global South.
It answers several questions.
How can developing countries prepare for and adapt to the transformative AI Revolution?
What are the requisite uptake enablers?
What about the potential inhibitors and barriers?
What constitutes an empowering AI ecosystem for emerging and least industrialised countries?
Furthermore, the book argues for identifying AI leapfrogging opportunities while advancing Global South-specific AI governance, regulations, and ethics.
The importance of regional and continental integration in the AI adoption strategy is also highlighted.
At the same time, specific recommendations are made on how private and public institutions should respond to and flourish under the AI revolution.
A case is made for research, development, production, and ownership of AI technology within the Global South.
Of course, the region must strive to adopt AI in all socio-political and economic sectors.
The book presents detailed discussions of such interventions in 11 sectors:
Education, Agriculture, Mining, Mobile Telephony, Legal Profession, Banking and Finance, Healthcare, Manufacturing, Infrastructure and Public Works, Tourism and Hospitality, and Governance.
Thus, the book addresses AI's value proposition to the developmental agenda of the Global South by focusing on its critical industries.
For each sector, the nature and manifestation of the challenges are discussed, and broad non-AI solutions are proffered first.
After that, potential AI-anchored interventions are advanced.
Countries in the Global South must learn from one another, both generally and specifically, with respect to the adoption and development of AI.
The book presents and reviews 10 case studies of countries from the developing world: China, India, Singapore, Rwanda, Malaysia, Mauritius, South Africa, Kenya, the United Arab Emirates (UAE), and Zimbabwe.
The objective is to harvest best practices from these countries' AI experiences and share the key learnings across the Global South.
With each case study, the country's general strengths and successes in its economy are reviewed, and lessons are drawn from them.
Thereafter, AI-based interventions are discussed, and key learnings are extracted.
Regional and continental AI efforts are also reviewed, particularly the African Union's (AU) blueprint, released in July 2024, titled "Continental Artificial Intelligence Strategy: Harnessing AI for Africa’s Development and Prosperity."
Similarly, the book provides a critique of the Final Report of the UN Secretary-General's High-Level Advisory Body, titled "Governing AI for Humanity: A Global Framework for AI Oversight". The document was released on 19 September 2024.
As a way forward, the book proposes that each country in the Global South develop and adopt a National AI Strategic Framework comprising six distinct but related components:
Vision, Strategy, Policy, Governance, Legislation and Regulation, and Implementation Matrix.
These national frameworks must be linked to similar and corresponding regional, continental, and beyond-continental ones.
Economies of scale and regulatory harmonisation must be at the centre of AI adoption.
For example, beyond their national AI efforts, Zambia and South Africa must leverage the Southern African Development Community (SADC), the African continent, Global Africa, and the Global South.
However, all these efforts will only succeed if anchored and driven by bold, visionary, strategic, and tech-savvy leadership at organisational, national, regional, continental and global levels.
Emerging and least industrialised countries need leaders who can create and articulate a clear, compelling, and technology-driven vision that inspires and motivates their citizens and institutions to achieve inclusive development and shared prosperity.
These transformational and innovative igniters and doers must possess a unique blend of foresight, passion, and innovation, enabling them to see beyond the current challenges of the Global South and anticipate AI opportunities, trends and challenges.
They must be adept at strategic thinking and possess a solid understanding of both history and geopolitics, particularly the complex and often exploitative relationship between the Global South and the Global North.
In this context, leaders from the Global South must take calculated risks and boldly pioneer economic transformation by embracing technology.
While humanity must anticipate, mitigate, and manage the threats posed by AI, it must also focus on leveraging AI to address global challenges.
However, the benefits of AI are not universally guaranteed worldwide.
The Global South must prepare for AI adoption and, indeed, plunge into implementation and execution.
Can AI create more problems than solutions in emerging and least industrialised countries, which have many easily automated jobs and a large informal sector?
For example, can the technology lead to job losses and higher unemployment, increasing inequality, poverty and marginalisation in the Global South?
This book proposes an approach to AI that will mitigate this potential risk.
The context and challenges of the Global South must be addressed while key AI enablers, including governance, regulations, legislation, ethics, and safety measures, are implemented to achieve this.
There must be reskilling of victims of job displacement, along with the development of new capabilities and competencies to take on AI-modified and entirely new AI jobs.
The number of modified and new jobs must exceed the number of destroyed ones.
The people and industries of the Global South must not just be consumers of knowledge, technology and innovations.
They must own and produce AI technology while pursuing the broad objective of applying AI across all their socio-political and economic sectors.
Although it is imperative and non-negotiable to embrace a broad range of enabling technologies, with a special focus on AI, it must be acknowledged that there are risks of technology-driven challenges such as digital imperialism and data colonialism, particularly in emerging and least industrialised economies.
Global South leaders must thoroughly understand and engage with decoloniality – a theoretical and practical framework aimed at dismantling the structures, knowledge systems, and power dynamics established during and after colonial rule, which are likely to influence the essence and content of AI systems.
Furthermore, it is essential to democratise AI – making the technology, tools, knowledge, and opportunities accessible to a broader range of people, communities, organisations, countries, and beyond, rather than being limited to a privileged few individuals, institutions, and economies.
Globally, democratising AI is the only way its benefits will be equitably spread worldwide, including in the Global South.
These emerging and least industrialised economies must have agency and proactively seek to deploy AI to achieve inclusive development and shared prosperity.
Yes, Artificial Intelligence can be the solution to challenges bedevilling the Global South.
This an Excerpt from the New Book Available at Amazon and Routledge – see the two Links below:
- Amazon: https://www.amazon.com/Artificial-Intelligence-Inclusive-Development-Prosperity/dp/1032833718/
**Professor Arthur G.O. Mutambara holds a PhD in Robotics and Mechatronics, and an MSc in Computer Engineering, both from the University of Oxford. He is a former deputy prime minister of Zimbabwe
*** The views expressed here do not necessarily represent those of Independent Media or IOL.
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