Artificial intelligence (AI) is rapidly transforming industries worldwide, but its explosive growth is now creating an unexpected challenge for consumers: a global shortage of RAM (Random Access Memory). Industry experts warn that this shortage is likely to push up the prices of smartphones, laptops, and computers over the next two years.
According to recent reports, ChatGPT emerged as the world’s most downloaded application, highlighting the unprecedented pace at which AI adoption is accelerating. However, the surge in AI usage has sharply increased demand for computing resources, particularly high-capacity memory. As AI companies acquire vast amounts of RAM to power and train their models, supply for consumer devices is shrinking, leading to higher costs.
AI’s Massive Appetite for Memory
Leading figures in the AI industry, including Sam Altman of OpenAI and Elon Musk of xAI, have repeatedly emphasized the growing need for processing power. Large-scale AI models require not only powerful processors but also enormous amounts of RAM.
While an average consumer laptop typically contains 16 GB or 32 GB of RAM, AI data centers often rely on systems equipped with thousands of gigabytes, sometimes several terabytes, of memory. This imbalance has created intense competition for available RAM supplies. Following earlier shortages of graphics cards, RAM has now become the next critical bottleneck for the technology sector.
Micron Shifts Focus Away From Consumers
The pressure on memory supply intensified after a major announcement by Micron, one of the world’s three largest RAM producers. The company revealed that it plans to stop selling certain RAM products to consumer markets, choosing instead to focus on large-scale AI data center clients.
Sumit Sadana, a senior executive at Micron, stated that the rapid expansion of AI infrastructure has dramatically increased global demand for memory. As a result, some consumer-grade RAM products may no longer be available after February 2026, marking a significant shift in the memory supply chain.
AI Firms Given Priority by Manufacturers
Other major memory manufacturers, including Samsung and SK Hynix, are also prioritizing AI-focused customers. These companies are increasingly investing in the production of high-bandwidth memory (HBM), a specialized type of RAM designed for AI workloads.
HBM offers significantly higher profit margins compared to traditional consumer RAM, prompting manufacturers to reduce the output of conventional memory modules. As AI companies are willing to pay premium prices, regular consumers are gradually being pushed to the margins of the market.
Sharp Rise in RAM Prices
The impact of this shift is already being felt. According to media reports, RAM prices could increase by three to six times by 2025. Other estimates suggest prices have surged by as much as 171 percent in just one year.
In India, for example, a 16 GB RAM kit is now selling for more than Rs 10,000 in major electronics markets such as Nehru Place, prices that were once considered unusually high. In smartphones, the cost of RAM has reportedly doubled, rising from around USD 35 to nearly USD 70 in some models. Analysts predict that prices could climb even further by 2026.
Higher Costs for Phones and Laptops Ahead
The rising cost of RAM is already influencing the pricing of consumer electronics. Newly launched premium smartphones are now retailing above Rs 70,000, compared with Rs 50,000-Rs 60,000 just a year ago. Laptop manufacturers such as Dell, HP and Lenovo are reportedly considering price hikes or adjusting their product lines.
Some companies are responding by reducing production volumes or releasing devices with lower RAM configurations to control costs. Industry observers warn that the global smartphone market could shrink in 2026 as higher prices dampen consumer demand.
In price-sensitive markets like India, where affordability plays a crucial role in purchasing decisions, the impact is expected to be particularly severe. As AI continues to reshape the technology landscape, consumers may soon find that the hidden cost of innovation is more expensive everyday devices.
