How AI Memory Demand Is Pricing a Billion Users Off the Internet

The Price of Intelligence

Somewhere between the data centers powering ChatGPT and the shelves of a shop in Lagos, a transaction is happening — one that rarely makes headlines. Every terabyte of AI training data requires memory. That memory competes with the smartphones that billions of people use to access the internet, apply for jobs, pay bills, and attend school.

The memory industry is choosing its winners. And they are not the poor.

DRAM and NAND prices have surged more than 300% year-over-year, according to IDC. The primary driver is unmistakable: AI data centers gorging on high-bandwidth memory and server-grade storage. Manufacturers are redirecting production capacity toward the highest-margin products — and the cheapest smartphones are the first casualty.

In Q2 2026, global shipments of sub-$100 phones fell roughly 60% compared to the same period last year. The sub-$100 segment isn’t cooling down. It’s disappearing.

IDC put it bluntly: the era of budget smartphones is over.

Africa Feels It First

The numbers hit hardest where the margins are thinnest. Africa, which depends on these devices more than any other region, saw smartphone shipments drop 7% in Q2 — and sub-$100 models plummet 34%.

Manish Pravinankumar, senior analyst at Omdia, said manufacturers simply cannot produce a $75 phone profitably anymore. Consumers who need internet access must now stretch their budgets to $200 or more.

For context, GSMA reports that in sub-Saharan Africa, an entry-level smartphone can cost up to 73% of a low-income worker’s monthly earnings. That is not a purchase. That is a triage decision.

Omdia noted that sub-$100 phones have served as the first mobile phone, the first internet device, and the primary mobile banking tool for hundreds of millions of Africans over the past decade. Remove that door, and the room beyond it — digital education, government services, online employment — locks itself.

A World Bank analysis published in May across 71 low- and middle-income countries found that smartphone owners were 34 percentage points more likely to access online education, government services, and job platforms than non-owners. The gap isn’t closing. It’s widening at the hinge.

The ripple effects extend beyond individual households. In Kenya and Nigeria, where mobile money platforms like M-Pesa and OPay have become infrastructure as vital as roads or electricity, declining smartphone ownership correlates with measurable contractions in financial inclusion. Young women, who already face steeper barriers to device access than men, are disproportionately affected — a dynamic that threatens to erase a decade of progress in gender-parity digital programs.

Schools in rural India and Pakistan that had begun integrating tablets and low-cost Android devices into curricula are now reverting to paper-based instruction. The equipment simply isn’t available at the price points these institutions can sustain, and donor-funded replacement cycles are stalling as budgets stretch thinner against rising component costs.

The Cost Structure Behind the Disappearance

Here is why the math no longer works for manufacturers. In a $99 phone, memory alone accounts for more than 64% of total component costs. When those memory prices triple, the phone either becomes unprofitable to build or impossible to sell at that price point.

The global average selling price of a smartphone is projected to reach $581 this year — up 27.6% from last year. That headline number masks a steeper reality at the bottom: the cheapest devices are being abandoned entirely rather than repositioned.

AI’s memory appetite is not a side effect. It is the central market force reshaping the entire smartphone supply chain, from fab allocation to finished-device pricing.

Samsung, SK Hynix, and Micron have all prioritized high-bandwidth memory and enterprise SSD production over the commodity DRAM and NAND that populate budget handsets. Fab time allocated to AI-grade chips carries a premium that commodity memory simply cannot match. The result is a structural reallocation — not a temporary spike — that industry insiders say will persist through at least 2028.

This isn’t speculation. Micron’s chief financial officer stated in May that enterprise and AI demand would continue absorbing capacity through the second half of the decade, with consumer-facing memory production growing only in proportion to what remained after enterprise allocations were satisfied. The ordering priority is explicit: data centers first, phones second.

How Buyers Are Adapting

Price shocks don’t just reduce demand. They redirect it.

In India, Counterpoint Research estimates that 42% of smartphone sales this year will go through installment plans or financing products — a signal that cash buyers are dropping out and credit-dependent buyers are filling the gap.

The refurbished market is growing faster than new shipments. Counterpoint reported that while new smartphone shipments fell roughly 11% in the first half of the year, the refurbished segment expanded 13%. Buyers who can no longer afford new budget phones are turning to devices that are a few years old but still functional — a segment manufacturers have effectively abandoned.

This is not a sustainable equilibrium. Refurbished supply is finite. Financing depends on credit access, which remains narrow in the very markets that need it most. The path forward for most low-income buyers is not clearer.

There are early signals of a secondary-market ecosystem emerging to fill the vacuum. In parts of Southeast Asia and East Africa, independent repair shops and informal distributors are beginning to salvage components from retired devices, creating a patchwork of modular parts that keeps older phones alive longer than they should function. It is an improvised solution — fragile, unregulated, and insufficient at scale — but it points to the kind of grassroots adaptation that tends to follow when formal markets retreat.

Some manufacturers are experimenting with stripped-down devices that sacrifice camera quality, screen resolution, and storage capacity to maintain a lower price point. But even these truncated versions require memory that is becoming prohibitively expensive. The engineering trade-offs are visible in test units reviewed by industry analysts: phones that boot slower, handle fewer apps simultaneously, and degrade in performance within months rather than years.

The Second-Order Fractures

The memory crunch is already producing consequences that extend well beyond the handset aisle.

App developers targeting emerging markets are recalibrating. WhatsApp Lite, Go’s XZ series, and a wave of new “data-light” applications are being optimized not because of genuine concern for low-bandwidth environments but because device manufacturers are shipping phones with less RAM and slower processors — constraints that force software to run leaner or not at all. The architecture of the internet itself is beginning to bifurcate: a high-performance tier for those who can afford capable devices, and a reduced-capability tier for everyone else.

Content platforms are noticing. YouTube, Facebook, and TikTok have all adjusted streaming defaults and compression algorithms for regions where device specifications are trending downward. The end result is a qualitatively different internet experience — lower resolution, fewer features, slower load times — packaged under the same interfaces wealthier users take for granted. This is not service degradation in the traditional sense; it is adaptive design responding to hardware scarcity. But the effect is the same: a two-tier information environment.

Even the environmental calculus is shifting. As new device sales slow and refurbished markets expand, e-waste management systems in developing nations — already underfunded and poorly regulated — face increased pressure. Old devices that once circulated through formal resale channels are now being discarded or informally dismantled, releasing toxic materials into communities that lack the infrastructure to handle them safely.

What This Means

The AI boom is often discussed in terms of compute power, model capabilities, and corporate investment. The distributional consequences arrive later and in quieter forms.

Right now, the consequence is this: a generation of first-time internet users in Africa, South Asia, and Latin America is being priced out of the cheapest possible entry point. The $100 phone was never about luxury. It was the floor. And the floor is being raised.

Memory manufacturers, smartphone OEMs, and AI companies are all making rational decisions within their own incentive structures. The irrationality is systemic — a market that treats connectivity as a premium good rather than a threshold utility is going to produce winners and losers along lines that have nothing to do with merit.

The question is not whether AI demand will continue to compress the budget segment. It is whether anyone is tracking what happens to the people on the wrong side of that compression.

The data is now clear. The sub-$100 smartphone is leaving the market. A billion users are watching the door close.

And unlike previous moments when access barriers fell — when CDMA replaced landlines, when feature phones gave way to smartphones, when 3G reached rural communities — there is no clear actor standing ready to replace what disappears. No public-private initiative large enough to absorb the gap. No policy framework designed for a world where the cost of basic digital participation is set not by manufacturing efficiency but by the procurement priorities of artificial intelligence.

The bottleneck is memory. The bottleneck is also attention.