Deploying Artificial Intelligence to Achieve the UN Sustainable Development Goals: Enablers, Drivers and Strategic Framework

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5 days ago

Professor Arthur G.O. Mutambara is the Director and Full Professor of the Institute for the Future of Knowledge (IFK) at the University of Johannesburg in South Africa.
Image: Supplied
The United Nations' Sustainable Development Goals (SDGs) are 17 interconnected goals designed to address the world's most pressing challenges by 2030. Adopted in 2015 as part of the 2030 Agenda for Sustainable Development, the SDGs cover a wide range of issues, including poverty eradication, quality education, gender equality, clean energy, climate action, and reduced inequalities. Each goal is supported by specific targets and indicators, providing a measurable framework for progress. The SDGs are universal, apply to all countries regardless of income level, emphasise the interconnectedness of global challenges, and thus require holistic solutions.
The SDGs are important because they provide a shared blueprint for global action and cooperation, uniting governments, businesses, and civil society to address critical challenges. By focusing on multidimensional goals, the SDGs encourage comprehensive strategies to tackle interconnected problems such as economic disparity, environmental degradation, and social inequities. They are vital for ensuring a sustainable future, reducing global inequality, and enhancing the quality of life for millions. Moreover, the SDGs emphasise leaving no one behind, targeting the most vulnerable populations, and ensuring progress benefits everyone.
However, there are challenges and complications. Progress towards achieving the SDGs has been mixed and uneven across different countries, regions, and goals. Indeed, significant advancements have been made in areas like poverty reduction, access to electricity, and improved healthcare. For example, global poverty rates declined steadily before the COVID-19 pandemic, and millions gained access to basic services such as clean water and education. Nevertheless, intractable problems are prevalent. Climate change continues to accelerate, inequality is rising, and many environmental targets, such as biodiversity conservation, are lagging behind. The COVID-19 pandemic and geopolitical conflicts, such as the unnecessary and avoidable wars in Ukraine, Gaza, and Sudan, have further slowed progress by disrupting economies, increasing inequalities, and redirecting resources away from SDG initiatives.
A significant barrier is inadequate funding. Achieving the SDGs requires trillions of dollars in investment annually, but many countries, especially low-income nations, lack the financial resources. Additionally, some regions' political instability, corruption, and poor governance hinder progress. The interconnected nature of the SDGs also means that failure in one area can impact others. For example, climate change exacerbates poverty and inequality, while conflicts and pandemics disrupt global efforts. Many countries' lack of data and monitoring capacity makes it challenging to track progress and identify effective solutions. The target date for attaining all 17 SDGs is 2030. It is a short five years away, yet according to the United Nations' 2024 SDG Report, only 17% of the SDG targets are currently on track to be achieved by 2030. Nearly half of the targets show minimal or moderate progress, while over a third are either stalled or regressing [132].
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Professor Arthur Mutambara's book "Artificial Intelligence: A Driver of Inclusive Development and Shared Prosperity for the Global South."
Image: Supplied
Indeed, the SDG agenda is characterised by an existential global crisis. So, what should be done? This book seeks to contribute to the resolution of this predicament. It aims to provide solutions to the challenges that have impeded the achievement of the SDGs by exploring broad and holistic interventions, technology-driven remedies, and, more specifically, the deployment of AI—the implementation of human intelligence in machines or systems programmed to perform tasks such as learning, reasoning, problem-solving, and decision-making. It is instructive to note that AI is just one tool. It is not a silver bullet. Achieving the SDGs by 2030 will require broader efforts and solutions than the use of AI systems.
Attaining the SDGs will depend on enhanced global cooperation, increased funding, improved infrastructure, and economic integration. Innovative solutions, such as leveraging technology and enhancing public-private partnerships, will be essential. The book proposes the acceleration of SDG progress by prioritising SDG implementation through stronger political commitment, integrated policies, and increased investment. There is a need to strengthen governance and policy frameworks. This ensures that resources are allocated efficiently, corruption is minimised, and accountability is upheld in implementing development programmes. Strong institutions, transparent decision-making, and inclusive policymaking are essential to ensure that progress towards the SDGs benefits everyone, particularly marginalised and vulnerable populations.
Countries must align their national strategies, policies, and budgets with SDGs, devising long-term plans to address interconnected challenges while ensuring inclusive and equitable policies. This includes enacting laws and regulations that promote equity, sustainability, and environmental conservation. Governments must introduce incentives for renewable energy adoption, enforce labour laws to reduce inequalities, and enhance land-use planning to protect biodiversity. There is a need to adopt innovations such as renewable energy for climate action and digital tools for education and healthcare. SDG progress can be driven by improving human capital through investments in education, healthcare, and social protection systems. Increasing funding for vocational training and public health campaigns can empower communities to address SDG-related challenges such as unemployment and public health crises.
International organisations, such as the United Nations and World Bank, must continue to support capacity-building and financial assistance for low-income countries. Achieving the SDGs requires bridging gaps between emerging or least industrialised economies and highly industrialised ones. There must be collaboration within the Global South and partnerships between the Global North and Global South. Global challenges like climate change, pandemics, and economic inequality require coordinated international efforts. Enhancing international cooperation and financing mechanisms is foundational to addressing funding gaps and sharing knowledge and resources for SDG implementation.
Highly industrialised countries must honour commitments to provide financial aid and technical support to emerging and least industrialised economies, mainly through mechanisms such as the Green Climate Fund and the Global Partnership for Education. There is a need to develop innovative climate financing models, including those based on carbon pricing such as carbon taxes, cap-and-trade systems, carbon markets, and green bonds. Fostering public-private partnerships can unlock investments in sustainable infrastructure, renewable energy, and other critical sectors. International trade policies should also be reformed to ensure fair market access for low-income countries. Strengthening multilateral institutions like the United Nations and World Bank is essential to coordinating global efforts, reducing systemic inequalities, and accelerating progress towards achieving the SDGs.
The arduous SDG journey towards 2030 will rise or fall on leadership. There is a need for visionary leadership at organisational, national, regional, continental, and global levels—characterised by the ability to create and articulate a clear, compelling future vision that inspires and motivates others to achieve the shared SDGs. It is essential for those driving the SDG agenda to have a unique blend of foresight, passion, and innovation, enabling them to see beyond the current reality and anticipate future trends and challenges. All this must be anchored by our shared common humanity and global interests, not narrow national, sectarian, or hegemonic interests. Unfortunately, events in the United States in early 2025 have signalled a shift from global collective leadership to isolationist, national interest-driven paradigms. US President Donald Trump signed executive orders to withdraw the United States from the Paris Agreement, the World Health Organisation, the UN Human Rights Council, and the United Nations Relief and Works Agency. He is also reviewing the country's role in the United Nations Educational, Scientific and Cultural Organisation and has moved to dismantle the United States Agency for International Development.
Achieving the SDGs in 2030 demands a different type of global leadership.
Technology (not necessarily Artificial Intelligence (AI)) is pivotal in advancing the SDGs by providing innovative solutions to global challenges. For instance, renewable energy technologies like solar panels, wind turbines, and hydropower systems are critical for achieving affordable and clean energy and combatting climate change. Similarly, advancements in water purification and sanitation systems directly address water and sanitation by ensuring access to safe drinking water and reducing waterborne diseases. Medical technologies, such as vaccines, portable diagnostic kits, and telemedicine platforms, are instrumental in advancing good health and well-being by improving healthcare access and disease prevention.
Desalination plants, water filtration systems, and wastewater recycling have significantly improved water security in arid and drought-prone regions. Drip irrigation schemes, bioengineered crops, and precision farming tools are transforming food production systems and reducing hunger. Emerging and least industrialised economies must move up the global value chains by implementing beneficiation and value addition. These two processes enhance the economic value of raw materials through local processing and manufacturing, generating higher revenues, creating jobs, and igniting sustainable development through the attainment of the SDGs.
The most significant contribution of this book is the use of AI to accelerate progress towards achieving the SDGs. Artificial Intelligence—the development of computer systems that can perform tasks typically requiring human intelligence, such as visual perception, speech recognition, decision-making, and language translation—is briefly introduced, and its unprecedented transformative nature is explained. The AI revolution is here. There were bold announcements on AI and its infrastructure in January 2025 from global leaders, such as UK Prime Minister Keir Starmer, then US President Joe Biden, and current US President Donald (immediately after his inauguration). Artificial Intelligence has become a key driver of competitiveness in every sector, and countries are unleashing massive investments in AI infrastructure. China's release, in the same month, of a ground-breaking open-source, low-cost, and less energy-intensive large language model called DeepSeek-R1, whose functionality is comparable to US offerings such as OpenAI's ChatGPT-4, Google's Gemini, and xAI's Grok 4, dramatises the equal-opportunity nature of the technology.
AI systems have the potential to provide innovative solutions to complex global challenges that impede the attainment of SDGs worldwide. For instance, AI-driven data analysis and predictive modelling can enhance decision-making processes across multiple SDG targets. In agriculture, AI systems can optimise crop yields by analysing weather patterns, soil quality, and pest activity, supporting the fight against hunger. These systems can guide farmers on when and where to plant crops, helping to reduce resource waste and adapt to climate-induced agricultural challenges. Similarly, AI-powered tools in supply chain management can minimise food loss and waste, ensuring that resources are used efficiently and equitably.
AI also plays a critical role in improving healthcare systems, contributing to good health and well-being. Machine Learning algorithms are used to detect diseases early, predict outbreaks, and personalise treatment plans based on patient data. For example, AI applications in medical imaging have proven highly accurate in diagnosing conditions like cancer and cardiovascular diseases. In addition, AI-driven tools enable the analysis of large-scale epidemiological data to predict the spread of infectious diseases, allowing governments to implement timely interventions. During the COVID-19 pandemic, AI was leveraged to track the virus's progression, develop vaccines, and optimise healthcare delivery in overburdened systems.
Furthermore, AI can advance climate crisis mitigation by supporting climate modelling and environmental monitoring. AI-powered tools can analyse satellite imagery to monitor deforestation, track changes in land use, and measure carbon emissions. These insights help policymakers implement targeted conservation efforts and design effective climate adaptation strategies. Additionally, AI can optimise energy use by managing power grids, improving energy storage, and integrating renewable energy sources like wind and solar into the grid. By reducing energy waste and emissions, AI technologies contribute to the global transition towards a low-carbon economy.
For quality education, AI-powered adaptive learning platforms provide personalised education tailored to individual learning styles and needs, making quality education accessible to marginalised communities. AI also supports gender equality by identifying and addressing systemic biases in hiring processes and enabling women entrepreneurs to access financial services through AI-based credit scoring. Moreover, AI-driven financial inclusion initiatives, such as mobile banking and digital payment systems, empower underserved populations, advancing decent work and economic growth. By deploying AI thoughtfully and equitably, governments and organisations can harness its transformative power to address global inequalities and achieve the SDGs.
The book addresses AI safety, regulation, legislation, governance, risk mitigation, and carbon footprint while reviewing the AI semiconductor industry. It also assesses AI's potential negative impact on the SDGs and examines the challenges of AI deployment. It emphasises aligning all national, regional, or continental plans with the AI-enabled SDG agenda. Summaries of AI-for-SDG experiences from six countries are outlined, and emerging best practices are harvested.
Details of enablers of AI deployment for SDGs are proposed and discussed—robust digital infrastructure and connectivity; awareness, education, and capacity building; regulations and ethical governance and accountability; guardrails; high-quality local data; financial resources and investment; beneficiation and value addition; research and development; and an accountable, capable, ethical developmental state. Similarly, critical mutually reinforcing drivers are presented: process efficiency and effectiveness; innovation and technological advancements; scalability and replicability; data-driven decision-making; addressing complex challenges; inclusivity and accessibility; partnerships and collaboration; private sector engagement; and policy support, governance frameworks, and global commitment.
Furthermore, it is essential to develop an AI ecosystem; embrace AI users' voices and insights; champion participatory approaches to AI design and deployment; incorporate diverse perspectives; and adopt feedback and iterative improvement mechanisms. There is efficacy in leveraging AI-enabled leapfrogging for SDGs, where emerging and least industrialised countries can bypass traditional stages of technological evolution and move directly to more advanced cutting-edge AI solutions. It is essential to embrace decoloniality in AI—a theoretical and practical framework aimed at dismantling the structures, knowledge systems, and power dynamics established during and after colonial rule, and likely to influence the essence and content of AI systems. In the same vein, it is imperative to democratise AI—making AI technologies, tools, knowledge, and opportunities accessible to a broader range of people, communities, and organisations beyond a privileged few.
Global governance for AI is vital. The key recommendations of the UN Secretary-General's 2024 AI Advisory Final Report are discussed. The strengths and flaws of this report are presented and explained. The principles of AI regulation/legislation and AI risk verticals are presented, while exemplary cases of AI legislation, such as the 2024 European Union AI Act, are reviewed, drawing lessons for other jurisdictions. However, the limitations of regulations and legislation as AI management tools are articulated, while the sociology of AI policy and adoption is also investigated.
While the book emphasises the need to embrace a broad range of enabling technologies, with a special focus on AI, it acknowledges the risks of technology-driven challenges such as digital imperialism and data colonialism, particularly in emerging and least industrialised economies. An incisive and robust case is made for decoloniality in AI on the SDG journey—a theoretical and practical framework aimed at dismantling the structures, knowledge systems, and power dynamics established during and after colonial rule and likely to influence the essence and content of AI systems. Furthermore, the book puts a premium on democratising AI in pursuit of the SDGs— making AI technologies, tools, knowledge, and opportunities accessible to a broader range of people, communities, organisations, countries, and beyond a privileged few individuals, institutions, and economies.
A key contribution of the book to AI adoption and thought leadership is the Strategic Framework for AI Deployment, which has six distinct but related components: Vision, Strategy, Policy, Governance, Legislation/Regulations, and Implementation Matrix (inclusive of Monitoring, Measurement, Evaluation and Feedback). In pursuit of the SDGs, every continent, regional bloc of states, country, organisation, or community must develop and adopt such a framework, where these structures dynamically influence each other. Within this context, the role of both regional and continental integration and political unity is articulated. The African Union's 2024 Continental AI Strategy is reviewed. Its strengths and weaknesses are discussed. The book provides details on deploying AI to achieve all 17 SDGs. Each goal is examined, its challenges are assessed, and detailed proposals for AI interventions to facilitate attainment are posited. AI adoption challenges and ethical considerations specific to the goal are discussed, and policy recommendations are proffered.
The potential future envisioned in the 2030 SDG agenda—a world free from poverty, hunger, and environmental degradation—is slowly becoming elusive, if not illusory. That desired future— complete attainment of the SDGs—is not inevitable. It is contingent on immediate and transformative action. Political and business leaders, policymakers, academics, civil society activists, and ordinary citizens must reignite momentum towards the SDGs, ensuring that 2030 becomes a milestone of achievement rather than a moment of regret. Global cooperation, regional/continental integration, moving up global value chains, inclusive economic transformation, addressing the climate crisis, and use of advanced technology (in particular AI) can play a significant role in the arduous journey to 2030.
Of course, there is the danger that AI will widen global inequality. Left unchecked, AI can intensify global disparities by consolidating power and wealth in affluent nations while exploiting labour and resources in emerging and least industrialised countries. There is a real possibility that AI will entrench existing inequities, leading to heightened political instability, environmental degradation, and cultural dominance by a select few. This book seeks to mitigate these challenges. AI must serve as a transformative force for the collective good, benefiting the entire planet and all its inhabitants in an equitable manner. Harnessing this transformative technology to advance the SDGs in every country offers a strategic and practical starting point. The UN Secretary-General, António Guterres, is right: 'We must never allow AI to stand for advancing inequality.'
This is an excerpt from the book "Artificial Intelligence: A Driver of Inclusive Development and Shared Prosperity for the Global South."
* Professor Arthur G.O. Mutambara is the Director and Full Professor of the Institute for the Future of Knowledge (IFK) at the University of Johannesburg in South Africa.
** The views expressed do not necessarily reflect the views of IOL or Independent Media.