Why UN Warns AI Could Deepen the Great Divergence
Across the Asia-Pacific, about a quarter of people lack online access, a massive gap compared to advanced digital economies like Singapore or South Korea. The United Nations Development Program just released a report highlighting how this digital divide risks deepening poverty rather than alleviating it, unless targeted infrastructure and skills investments happen fast.
While AI promises productivity gains and better healthcare, the report exposes a brutal reality: the biggest beneficiaries today are wealthy countries with reliable power, internet, and data ecosystems. But the critical dynamic at play isn’t technology itself—it’s the uneven access to foundational systems that enable AI leverage.
This matters because AI, like electricity or internet before it, becomes an essential infrastructure platform that compounds advantage for those already well-connected. Countries controlling this infrastructure shape economic fate.
“We tend to overemphasize technology. It’s people first,” sums up Michael Muthukrishna, report lead from the London School of Economics. Without shifting focus, the AI revolution risks mirroring the 19th-century industrial Great Divergence—accelerating inequality rather than bridging it.
Rethinking AI as a Productivity Panacea Misses the Core Constraint
Conventional wisdom praises AI as a productivity booster that naturally lifts all boats. That’s why many investors and policymakers race to adopt AI tools, expecting trickle-down benefits.
They overlook the structural constraint: without digital infrastructure and skills, AI systems cannot even operate effectively in marginalized regions. This is constraint repositioning, not simple cost-cutting or innovation timing. For example, Afghanistan and Myanmar lack stable power and internet, making AI deployments infeasible regardless of potential.
Contrast that with Asian hubs like China and Japan, where robust infrastructure lets AI scale quickly into healthcare, agriculture, and disaster response. See how AI reshapes labor dynamics in these ecosystems rather than simply replacing jobs.
AI’s Leverage Lies in Infrastructure-as-Platform and Data Inclusivity
AI’s true leverage emerges only when infrastructure platforms and data environments include disconnected communities. For instance, AI-enabled rapid X-ray analysis or weather forecasting offers enormous value in rural Asia-Pacific areas prone to natural disasters, but only if real-time data flows and digital skills exist.
Unlike wealthier countries, those regions face “invisible” populations absent from data sets, undermining AI’s learning loops. Without foundational investments, the compounding mechanism of AI—continuous learning from diverse, up-to-date data—breaks down, leaving millions excluded from the global economy.
Internal constraints here shift from just AI tech to the very pipeline of data and electricity needed to sustain AI as a public value engine.
The trade-offs also extend to environmental impact. Data centers in the United States and Europe risk consuming excessive electricity and water, clashing with sustainability goals. This constraint forces a choice between AI scale and climate commitments.
This digital infrastructure complexity exposes a key leverage gap, as seen in the cybersecurity challenges recently discussed in Anthropic’s AI hack analysis. Without systemic security and regulatory guardrails, the platform risks amplifying harm.
Closing AI Gaps Requires Governments to Build Digital Foundations First
Changing the constraint from AI access to digital foundation flips the growth playbook. Instead of chasing AI tools alone, investing in power grids, internet access, data transparency, and digital literacy becomes the strategic lever to democratize AI benefits.
Governments in Asia-Pacific must, like Singapore or South Korea, treat AI infrastructure as critical public infrastructure—similar to roads or electricity. That means financing social protections and competitive markets for AI-enabled services to scale inclusively.
For operators, the new shortcut is clear: leverage AI only where foundational systems exist and expand the base by addressing connectivity and skills gaps. This reframing clarifies who wins and loses in AI adoption, making the invisible foundation visible.
Other regions can replicate this model, making basic digital infrastructure the real competitive moat behind future AI growth. Operational leverage starts with systems that empower everyone, not just advanced economies.
“Technology follows, but empowerment leads—any AI strategy ignoring that is doomed to deepen divides,” concludes Philip Schellekens, UNDP economist.
The future won’t be AI first. It will be systems that build AI leverage for all.
Related Tools & Resources
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Frequently Asked Questions
Why does the UN warn that AI could deepen the Great Divergence?
The UN Development Program warns that about 25% of people in Asia-Pacific lack internet access, which limits equitable AI benefits. Without targeted investments in infrastructure and skills, AI technology risks accelerating inequality rather than reducing it.
How does digital infrastructure affect AI adoption?
Digital infrastructure like stable power grids and internet access are foundational for AI systems. Countries with robust infrastructure like China and Japan can scale AI more effectively, while regions lacking these basics, such as Afghanistan and Myanmar, face infeasible AI deployment.
What role do data inclusivity and digital skills play in AI’s impact?
AI relies on continuous learning from diverse, up-to-date data and requires digital literacy to function effectively. Marginalized populations absent from data sets undermine AI’s learning, leaving millions excluded from economic benefits unless foundational investments improve data inclusion and digital skills.
Why is AI compared to electricity and internet in this context?
AI is considered an essential infrastructure platform similar to electricity and internet because it compounds advantages for those with access. Countries controlling these infrastructures influence economic outcomes, emphasizing the need for broad digital foundation investments.
What are the environmental challenges associated with AI scale?
Data centers in the US and Europe consume large amounts of electricity and water, which can conflict with climate goals. This creates a trade-off between expanding AI infrastructure and meeting sustainability commitments.
What strategies can governments use to close the AI access gap?
Governments should prioritize building digital foundations such as power grids, internet access, and digital literacy. Treating AI infrastructure as public infrastructure, like roads or electricity, and financing social protections can help democratize AI benefits.
How do cybersecurity concerns relate to AI infrastructure?
Without systemic security and regulatory guardrails, AI platforms risk amplifying harm, as highlighted by recent cybersecurity incidents like Anthropics’ AI hack. Secure infrastructure is critical to safely scaling AI technologies.
Can other regions replicate Asia-Pacific’s approach to AI infrastructure?
Yes. The article suggests replicating Asia-Pacific’s focus on basic digital infrastructure as the real competitive advantage for AI growth. Building inclusive systems empowers all regions beyond just advanced economies.