Artificial intelligence (AI) has redefined global competition in the 21st century. While AI innovation advances at breakneck speed, international governance mechanisms lag far behind. Fragmented national regulations, unilateral semiconductor export curbs, and stark inequities in access to computing power have forged a new global rift: the AI divide.For Africa and the broader Global South, the core debate has moved past mere access to AI technology. The critical question is whether developing nations will possess a seat at the table to shape global AI rules. Discussions at the 2026 AI for Good Global Summit, the World Summit on the Information Society and other multilateral forums have circled this core tension. A report from the UN’s Independent International Scientific Panel on AI underscores that today’s AI gap extends well beyond hardware. It manifests as systemic imbalances in governance influence, industrial capacity, and participation in international rule-setting. Countries locked out of drafting AI standards risk permanent dependency on foreign technologies, surrendering autonomy over their digital development trajectories.
China’s multi-tiered AI governance vision
Against this unequal backdrop, China has rolled out a structured global AI governance framework that balances technological innovation, security safeguards and the right to development, specifically designed to address the underrepresentation of Global South states.
Launched in 2023, the Global AI Governance Initiative lays the foundational ethos: human-centric AI progress, full respect for national sovereignty, equal standing for all countries regardless of size or wealth, and rejection of exclusionary technological barriers. It advocates building a formal international AI governance mechanism within the core UN framework. At the 2025 World Artificial Intelligence Conference in Shanghai, China released the Global AI Governance Action Plan, enshrining six official guiding tenets: people-centered development, sovereignty prioritization, development-driven innovation, safety and controllability, fairness and inclusivity, and multilateral collaboration.
This architecture stands apart from Western governance models, which often treat developing countries as passive recipients of technology. Instead, it positions emerging economies as equal co-creators of AI innovation. Complementing these frameworks, the 2025 AI Plus International Cooperation Initiative targets six high-priority livelihood sectors across the Global South: agriculture, healthcare, education, disaster risk reduction, industrial upgrading and talent cultivation.
The China-Mozambique precision agriculture project in the Gaza province offers tangible proof of this model’s value. Leveraging Beidou satellite navigation and drone farming tools, the initiative has delivered substantial, sustained rice yield growth for local communities. For most African nations, practical, people-focused AI use cases carry far greater weight than abstract theoretical debates over cutting-edge large models. China has additionally proposed establishing a World AI Cooperation Organization, and evolved the World AI
Keep Reading
- Time running out for SA-based Zimbos
- Sally Mugabe renal unit disappears
- Epworth eyes town status
- Commodity price boom buoys GB
Conference into a permanent multilateral dialogue platform. It serves as a valuable supplement to UN-led governance, giving Global South states a dedicated space to negotiate standards rather than blindly adopting rules crafted by advanced economies alone.
Three structural barriers facing African AI advancementAfrica confronts three entrenched structural roadblocks on its path to AI self-sufficiency.
First, a pervasive capacity gap. Competitive AI ecosystems rely on robust computing infrastructure, skilled technical workforces, established research institutions and tailored regulatory systems — all areas where African states face widespread shortages.
Second, artificially engineered technological fragmentation. Unilateral restrictions on advanced semiconductors and high-performance computing from certain developed economies erect discriminatory digital barriers that disproportionately undermine developing countries’ right to progress. Context is vital here: all nations implement moderate technology controls to safeguard domestic security, and such prudent risk management must not be conflated with sweeping, exclusionary blockades. Unregulated AI expansion carries transboundary hazards including deepfake abuse, data breaches and algorithmic bias; balancing development and security remains a shared global imperative.
Third, disjointed global regulatory standards. Every state enacts AI legislation aligned with its unique political and legal frameworks, pushing up cross-border compliance costs for businesses and governments while creating persistent policy uncertainty.
These hurdles are not without countervailing opportunities. Open-source large language models such as DeepSeek and Qwen have drastically cut the financial barriers to AI research, granting affordable access to advanced technology for African universities, local startups and public authorities. Open-source ecosystems deliver more than low-cost tools; they empower nations to build digital sovereignty and design localized AI systems attuned to indigenous languages and regional development priorities. That said, open-source models carry inherent limitations — algorithmic bias, data vulnerabilities and persistent underlying computing costs — and cannot function as a one-size-fits-all fix for systemic development gaps.
A five-step roadmap for the Global South to claim AI agency
Africa and other Global South economies must act decisively to seize the transformative window created by AI, following five clear strategic steps.Governments should formulate national AI strategies that reconcile innovation incentives with ethical risk oversight, and actively contribute to multilateral rulemaking to amplify developing-world perspectives.
Policymakers should harness open-source technology to build region-specific applications, scale AI literacy programmes and cultivate indigenous research talent pipelines.
AI investment should be directed toward pressing livelihood challenges: precision farming, grassroots medical services, inclusive education, early disaster warning systems and climate resilience.
States should engage fully with multilateral AI governance forums to ensure global standards reflect diverse developmental contexts, dismantling the monopoly of rule-setting held by a small cohort of advanced economies.
Regional blocs including the African Union, ASEAN and CELAC, alongside multilateral bodies such as the BRICS and SCO, should deepen South-South collaboration through joint research, shared expertise, coordinated diplomatic stances and regional capacity-building schemes.