Sridhar Vembu explains why phones and laptops are getting expensive in 2026

Sridhar Vembu has warned that the AI boom is no longer just a story about chatbots, GPUs and billion-dollar data centres. It is beginning to show up in the price of everyday technology. Smartphones, laptops and other gadgets are becoming more expensive as AI companies pour huge amounts of money into data centres and compete for the same memory and semiconductor capacity used by consumer devices, Zoho founder Sridhar Vembu said in a social media post.

The result is an unusual situation for technology buyers in 2026. The same investment wave that is helping build more powerful AI systems is also putting pressure on the supply of components needed to make phones and laptops. Memory prices have risen sharply, while manufacturers are dealing with higher costs and tighter supplies.

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AI data centres are changing the chip market

Vembu feels that the reason starts with the enormous amount of hardware needed to run modern AI systems. Technology companies are spending hundreds of billions of dollars on AI infrastructure, including servers, GPUs, networking equipment and high-performance memory. Goldman Sachs economists estimate that AI investment could reach around $600 billion in the US alone in 2026.

"The sticker shock seen by anyone trying to upgrade their smart phone or laptop in 2026? That is the AI investment boom, funded (ultimately) by the mother of all credit bubbles unleashed post pandemic. It has distorted markets ranging from electric power generation, transformers, diesel back up generators, cooling systems, memory, CPUs and of course, GPUs," Vembu said on X.


This spending has created a new priority for chip manufacturers. AI data centres need specialised memory, including high-bandwidth memory, as well as large quantities of other semiconductor components. That matters because chip manufacturing capacity is not unlimited.

As manufacturers allocate more production towards the lucrative AI market, consumer electronics companies can face tighter supplies of memory and other components. IDC has warned that the shift in production towards AI-related memory is affecting the supply available for smartphones and PCs.

Your phone and laptop are caught in the middle

Smartphones and laptops also need memory chips. When the price of those components rises, manufacturers eventually have to decide whether to absorb the extra cost or pass it on to buyers. Many are choosing the latter. The memory crisis has already pushed up the cost of consumer electronics, with reports indicating that manufacturers have increased prices for products ranging from smartphones and tablets to laptops and gaming consoles.

So, when a buyer looks at a more expensive laptop in 2026, the reason may not simply be a better processor or a new design. Some of the increase can be traced back to a much bigger race taking place inside data centres.

Memory has become the new pressure point

Memory is particularly important because AI systems consume enormous amounts of it. The shift has helped create what some industry observers are calling “chipflation”, a period in which semiconductor prices are rising instead of following the long-established pattern of becoming cheaper over time.

Axios reported that the surge in memory demand is affecting smartphones, laptops, cloud storage and other hardware. Morgan Stanley has also estimated that PC and smartphone prices could see significant increases because of higher component costs.

That reverses a familiar pattern in consumer technology.

For years, buyers generally expected each generation of phones and computers to offer more memory and processing power for roughly the same money. The AI boom is putting pressure on that model.

Even software companies are feeling the impact

The problem is not limited to device manufacturers. Zoho founder Sridhar Vembu also warned about the rising cost of memory and AI tokens, saying that the combination was making business increasingly difficult.

“Memory prices, along with AI token prices, have made business very difficult. We have held back from raising prices but it is becoming hard,” he wrote.

Vembu also argued that the era of treating memory as an inexpensive resource may be coming to an end.

“For a long time, programming languages were designed with the assumption that memory is ‘free.’ That era has now ended,” Vembu added.

His comments highlight how the cost of the AI boom is spreading beyond the companies directly building AI models.

The bigger question is whether the AI spending can continue

There is another side to this story. AI technology itself is real, and demand for AI services continues to grow. Companies are investing in data centres because they expect AI to become a major part of computing and business.

But the scale of the investment has also raised questions about whether the current spending cycle can continue indefinitely.

The AI infrastructure boom is creating demand for GPUs, memory, electricity, cooling equipment, networking hardware and data centre construction. That creates opportunities for manufacturers, but it can also push up costs across the technology supply chain.

The situation is somewhat similar to earlier technology investment booms, where the underlying technology eventually became widespread even though many companies that invested heavily in the initial frenzy did not survive.