AI often appears to be immaterial; a black box of code, data, and neural networks. However, the reality is that these algorithms are built on immense amounts of mined minerals, semiconductors, and energy intensive data centers. As AI demand surges, it is quietly reshaping global semiconductor markets and shifting cost pressures downstream to consumers.
The release of ChatGPT in late 2022 significantly accelerated the diffusion and visibility of AI technologies globally, including in African contexts. Organizations have since been compelled to embed AI solutions in routine tasks, harnessing its potential to accelerate, optimize, and automate workflows.
Individuals are increasingly incorporating AI tools into their daily lives to enhance productivity, support personalized learning, provide virtual assistance, and creative work. Demand has scaled at extraordinary speed, outpacing traditional semiconductor supply.
The AI boom has reshaped the global semiconductor market with AI chips forecasted to account for 20% of the $450bn market. The challenge lies in the fact that both conventional DRAM used in consumer electronics and high bandwidth memory (HBM) used in AI accelerators rely on similar manufacturing processes and production capacity.
Leading memory chip producers such as Samsung, Micron, Hynix, and CXMT have diverted a growing share of their production capacity toward high bandwidth memory (HBM) chipsets used by Nvidia and Advanced Micro Devices (AMD).
Nvidia disclosed in August 2025 that the demand for AI chips to furnish data centers drove second-quarter revenue to $41.1bn up 56% from a year ago, illustrating the exponential growth in demand for these advanced chips. With advanced semiconductor fabrication concentrated in a handful of companies, capacity constraints are amplified when AI chips dominate production queues.
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The shift in production capacity has structural consequences for the broader electronics market. Fabrication lines that would traditionally support smartphone, tablet or laptop manufacturing pipelines are allocated to HBM stacks used in AI data centers.
According to the International Data Corporation (IDC), original equipment manufacturers will likely have to raise prices significantly to offset rising component cost as well as the now constrained supply. This spells trouble for African consumers, as it suggests that the cost of digital devices will rise, further straining limited purchasing power.
In Africa, smartphones are primary gateways to financial services, education platforms, digital work, and social communities. While some industry reports estimate that the average selling price of a smartphone could rise by 3% to 8% in 2026, more pessimistic projections estimate increases of 10% to 15%. The effect isn’t limited to smartphones. Laptops, desktops, and tablets are also experiencing price bumps.
The upward pressure facing consumer electronics pricing may deepen existing digital affordability gaps. These increases are felt disproportionately in markets outside the industrialized world, where import taxes, foreign exchange pressures and thin profit margins magnify price movements at the consumer level.
Without interventions to stabilize device affordability, the very populations best poised to benefit from AI may find themselves priced out of the digital economy at entry level. Yoshua Bengio, a godfather of AI, cautions that “AI is a powerful technology and a force for good, but it is important to be conscious of its growing sustainability impact.” That impact carries a cost, and much of that cost is set to be borne by the consumer.
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