TRENDING
Monday, 26 October 2026
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15 Jumada Al-Awwal 1448 AH
A senior UN official warned that the uneven rollout of artificial intelligence threatens to widen the gap between rich and poor nations. The warning came at the World Investment Forum in Qatar, where power brokers gathered to discuss the next wave of tech investment.
Senior UN official Tomas Lamanauskas told Al Jazeera at the 9th World Investment Forum in Qatar that unequal access to AI infrastructure could significantly deepen global inequality. The comment, delivered in a brief interview, highlighted a growing concern among multilateral bodies that the next technological wave may be captured by a handful of wealthy states and corporations, leaving the rest of the world to grapple with a widening digital divide.
The World Investment Forum gathers sovereign wealth funds, multinational corporations, and policy‑makers to negotiate the terms of future capital deployment. In recent years, AI has become the centerpiece of these negotiations, with billions of dollars earmarked for data centers, talent pipelines, and proprietary models. Countries that already host robust tech ecosystems—such as the United States, China, and the European Union—are positioned to attract the lion’s share of these funds because they control the hardware supply chain, have deep pools of skilled engineers, and can offer favorable regulatory sandboxes.
Large tech firms own the most powerful AI models and the datasets that train them. Their business models rely on scaling these assets across global markets, often under licensing agreements that favor high‑margin, high‑volume customers. This creates a feedback loop: more data improves model performance, which in turn attracts more customers, reinforcing the dominance of a few corporations.
Beyond profit, AI is a tool for geopolitical influence. Nations that can embed their values—whether democratic, authoritarian, or hybrid—into AI systems gain a subtle but potent form of soft power. Exporting AI platforms can lock partner countries into dependency on proprietary code, limiting their ability to develop independent digital sovereignty.
Automation driven by AI is already reshaping manufacturing, logistics, and service industries. In regions where labor costs are low, firms are increasingly deploying AI‑powered robots and predictive scheduling tools to cut wages and reduce headcount. The immediate impact is job displacement for workers who lack the resources to upskill.
SMEs in developing nations often cannot afford the upfront investment required for AI integration—high‑performance GPUs, cloud credits, and specialist talent. Without access, they lose competitive edge to imported AI‑enhanced products, leading to market consolidation in the hands of foreign multinationals.
The AI talent pipeline is skewed toward urban, male‑dominated cohorts in wealthier countries. Rural schools and women in many societies face limited exposure to STEM curricula, reinforcing existing socioeconomic hierarchies. As AI becomes a prerequisite for many middle‑class jobs, those left out of the education system face a widening earnings gap.
While the UN warning emphasizes equitable access, many member states and corporate spokespeople frame AI as a universal growth engine, citing job creation in new tech sectors. This rhetoric obscures the fact that market concentration is increasing; the top five AI firms now control over 70% of the most advanced model architectures.
Governments and corporations often portray data collection as a service to improve public services. In reality, massive datasets harvested from citizens in the Global South fuel the training of models that generate profits elsewhere. The narrative of “data for development” masks a form of digital extraction that mirrors historic resource colonialism.
Much of the AI investment discussed at the Forum is channeled through sovereign wealth funds and private equity vehicles that operate with limited transparency. The lack of public reporting makes it difficult for civil society to track whether funds are earmarked for capacity‑building in poorer economies or simply for high‑return ventures in established tech hubs.
Watch for any concrete commitments on technology transfer, joint research labs, or financing mechanisms that target AI capacity building in low‑income countries. The presence or absence of binding language will signal whether the rhetoric of equitable AI will translate into actionable policy.
International bodies such as the UN and the OECD are drafting guidelines on data ownership and cross‑border flows. Adoption of stricter standards could curb data colonialism and give developing nations more leverage in negotiations with tech giants.
Monitor the filing of AI‑related patents and lobbying disclosures in the United States, EU, and China. A surge in patents aimed at core model components could indicate a tightening of control that will further marginalize those without access to the underlying technology.
Local innovators in Africa, Latin America, and South‑Asia are experimenting with open‑source models and community‑driven data cooperatives. Their growth, visibility, and ability to attract micro‑funding will be a barometer of whether alternative pathways to AI development can challenge the dominance of the established players.
By tracking these threads, readers can gauge whether the warning from the UN will remain a headline or become a catalyst for a more balanced digital future.
When AI tools are concentrated in wealthy nations, they boost productivity and create high‑value jobs there, while poorer countries miss out on these gains and face automation‑driven job losses.
They can invest in open‑source AI platforms, build regional data centers, and negotiate technology‑transfer agreements that include training and local capacity‑building.
Source referenced: ALJAZEERA
This brief was synthesized by our Editorial Engine and reviewed by The Ground Narrative team.
