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Ongoing AI development is creating a supply shock that simply cannot be circumvented or avoided in 2026, GenInnov CEO Nilesh Jasani explains.
- Today's silicon shock has parallel's with early 2000's demand explosion for aged whiskey
- Sudden acceleration in demand creates unsolvable supply shortages
- Product prices have only one way to go; up
- How long before consumer electronics are re-priced?
By Nilesh Jasani, CEO GenInnov
In the early 2000s, the world of fine spirits broke. Demand for aged whiskey and fine wine exploded with new wealth, new buyers, and a global culture shift.
Everyone could see it happening. But supply could not respond because supply had been “decided” years earlier when the barrels were filled. No amount of money could speed up a calendar.
The result was violent. Prices did not just rise; they decoupled from reality.
Today, we are walking into the exact same trap. But this time, it is not about luxury consumables. It is about the fundamental substrate of the modern economy. It is about silicon.
We are witnessing a Silicon Shock. It is happening now. It is happening at a scale that makes the whiskey crisis look like a rounding error.
Unlike the 1970s oil shocks, which were driven by supply embargoes, this crisis is driven by a ferocious, unyielding explosion in demand. The world has suddenly realized it needs to convert sand into “intelligence” at a rate that defies physics.
The demand for compute, specifically the high-performance silicon required to process AI tokens, has not increased by 50% or 100%. Depending on how you measure the fundamental unit of AI thought, demand has exploded by anywhere from 40 to 100 times in the last 18 months.
Even if you cut the headline numbers and use a conservative blend, you still land in the range of 40 to 60 times growth.
The supply chain cannot hold. It is breaking. Building a new fabrication plant takes three to five years. Expanding high-bandwidth memory production takes two to three years. Adding advanced packaging capacity takes 18 to 24 months. After exhausting spare capacity and drawing down inventories to crisis levels, the world has reached a point where the bottlenecks are multiplying.
The primary reason the market has miscalculated the severity of this shock is a fundamental misunderstanding of what is consuming the silicon.
For most of 2023 and 2024, the mental model for AI demand was “human-speed” interaction: a user types a prompt into a chatbot, the chatbot replies, and the transaction ends. That era is over. In late 2025, the nature of the workload shifted fundamentally.
We moved from Chatbots to Agents, and from Pattern Matching to Reasoning. The new dominant workload is “Agentic AI.”
These systems do not wait for a prompt. They run in continuous, autonomous loops while planning, executing, checking, and correcting. A single instruction from a human can trigger a cascade of thousands of internal inference steps running 24 hours a day, invisible to the user but punishing to the hardware.
Simultaneously, the integration of AI into “default” surfaces has converted billions of trivial interactions into heavy inference tasks. When Google switched its Search AI Overviews to reasoning-enhanced models, it applied compute-intensive inference to over 4 billion daily queries.
A single decision converted low-cost keyword lookups into high-cost generative tasks. Multiply this across Microsoft’s Copilot, Meta’s WhatsApp, and Tencent’s WeChat, and the aggregate demand becomes astronomical.
Some observers may dismiss the silicon shock as the frothy excess of an AI bubble. This critique misunderstands the nature of the demand.
This shortage is not a speculative buildout of empty data centers financed cheaply. It is an operational inference load from real users generating real tokens in real applications.
AI is not a product that will be abandoned when funding tightens; it is becoming infrastructure.
The most insidious part of the Silicon Shock is the “Cascade Effect.” Because AI demand is effectively infinite and price-inelastic, the semiconductor industry has rationalized its entire production line to serve AI.
Samsung and SK Hynix are actively converting production lines away from standard consumer memory to make High Bandwidth Memory (HBM) for AI accelerators.
This is the “Vampire Effect”: AI is sucking the lifeblood out of the rest of the electronics market. The result is a shortage of the “boring” chips used in laptops, phones, and cars.
Prices for standard RAM are skyrocketing because the wafers are being used for AI instead. Industry memory inventory levels fell from roughly 15 weeks in late 2024 to just 2 to 4 weeks by October 2025. There is no cushion remaining.
In the last eight weeks alone, the whispers turned into screams. We counted executives from nearly twenty major firms, ranging from chipmakers like TSMC and Micron to consumer giants like Dell and Xiaomi, all expressing the same alarm.
They are no longer hiding the problem; they are pricing for it.
Jeff Clarke, the COO of Dell, warned that they “have never seen memory chip costs rise this fast,” noting that demand is way ahead of supply. Sanjay Mehrotra, the CEO of Micron, stated that his company can only meet “50% to two-thirds” of the demand from its main customers.
The situation is even more dire at the foundry level. C.C. Wei, the CEO of TSMC, has stated that capacity is “3x short” of demand.
Perhaps most telling is the comment from Chey Tae-won, Chairman of SK Hynix. He admitted that they are receiving so many requests for memory that they are worried about how they will be able to handle it, warning that clients could face a situation where they “can’t do business at all” without supply.
A Winbond executive noted that customers are now begging for six-year supply agreements, a level of panic rarely seen in modern supply chains.
We are staring down the barrel of a supply chain crisis that looks less like a tech cycle and more like a geopolitical resource shock. One has heard a lot about the “Power Wall” —power shortages for AI centers— in recent quarters. These are, to some degree, solvable problems with human ingenuity or regulatory changes.
We cannot think of any half-decent solution for the Silicon Shock the world has entered into.
The factories required to solve this problem have not yet been built. What is being planned for the coming years is not remotely sufficient if demand growth remains on the same trajectory.
The die is cast. The shortage is here. Just like the oil shocks of the past, the pain is about to cascade from the data center down to your laptop, your phone, and your wallet.
Silicon may or may not be the new oil, but Silicon Shock has the potential to be a dominant macro, political, and market theme of 2026.
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The above is an abbreviated version of Nilesh Jashani’s latest update on what’s moving in today’s AI development. The full version: https://www.geninnov.ai/blog/silicon-shock-the-big-26-theme
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Nilesh Jasani
CEO, GenInnov
LinkedIn: https://bit.ly/3zQpCnZ
GenInnov Articles: www.geninnov.ai/blog
Re-published with permission. Views expressed are not by association FNArena’s.
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