Summary
SEMICON India 2026 took place amid what analysts call an AI-driven semiconductor supercycle. Microsoft, Amazon, Google and Meta plan to spend nearly $635 billion on AI infrastructure in 2026 and chipmakers are signing long-term take-or-pay contracts.
The boom rests on AI accelerators paired with high-bandwidth memory (HBM), joined through advanced packaging. HBM is dominated by SK Hynix, Samsung and Micron. India does not fabricate chips. ISM 1.0 approved 12 projects focused on assembly, testing and packaging.
ISM 2.0, launched in February 2026, supports advanced packaging and chiplet R&D. It also builds on India's share of nearly a fifth of the global chip design workforce, which is illustrated by Infineon's acquisition of the Bengaluru fabless firm C2i.
WHY IN NEWS FOR UPSC & STATE PCS
An Expert Explains piece in The Indian Express by Carnegie India's Shruti Mittal, published after SEMICON India 2026 in New Delhi, asked what the AI chip supercycle means for India. A parliamentary reply in July had said that demand for AI servers and data centres was tightening memory supply and raising prices.
Some foreign investment withdrawals from Indian markets in 2026 have been linked to interest in the semiconductor-heavy markets of Taiwan and South Korea.
Standard News
The Bottleneck in AI Chips Is Moving Data Between Memory and Processor and That Is Where India Has an Opening
Here's what is actually happening inside an AI data centre. The processor, the AI accelerator, can do calculations extremely fast. Its problem is that it often waits for data. Traditional memory sits some distance from the processor on the circuit board and moving huge volumes of numbers back and forth across that gap is slow and energy-hungry.
Engineers call this the memory wall. For AI workloads, the memory wall rather than raw processing power often decides how fast a model runs.
The mechanism:
bring the memory closer High-bandwidth memory (HBM) addresses the problem by stacking layers of memory chips vertically, connected by tiny electrical channels drilled through the silicon and placing that stack right next to the processor. Advanced packaging is what makes this possible: the processor and memory stacks are mounted together on a shared base layer so that data travels a short distance at very high bandwidth.
A useful analogy is a chef (the processor) whose pantry (the memory) used to be down the corridor. HBM puts stacked shelves right beside the stove and packaging is the kitchen layout that makes it work. Where the analogy stops working: a chef walks to fetch ingredients, but chips move data as electrical signals and the real engineering difficulty is heat, signal integrity and manufacturing yield when stacking and bonding chips at microscopic scale.
Designing a kitchen is easy by comparison. That is why the supercycle is not only about leading-edge fabs. Value is shifting toward memory stacking and packaging, which are the steps that turn separate chips into a working AI system.
Where
India stands Behind on leading-edge fabrication. India does not produce advanced chips and HBM is controlled by three firms: SK Hynix, Samsung and Micron. Building in packaging. ISM 1.0 approved 12 projects with an emphasis on assembly, testing and packaging.
Micron's Sanand facility in Gujarat will process imported wafers. ISM 2.0 now adds support for packaging and R&D in chiplets, which combine smaller specialised chips instead of one large piece of silicon. That lowers cost and waste and the benefit grows as chips get more complex. Ahead in design talent.
Nearly a fifth of the global chip design workforce is in India. Startups such as Netrasemi are designing edge-AI processors under the design-linked incentive scheme. Germany's Infineon has acquired Bengaluru's C2i, whose power-management designs for AI data centres show that Indian design work is already part of the AI hardware supply chain.
The honest caveat Being in the chain is not the same as capturing its value.
When a global firm buys an Indian design startup, the intellectual property and much of the future profit, moves with it. And the supercycle depends on spending by a few companies; if AI revenue disappoints, the boom could slow.
Quick Facts
Key numbers & takeaways — revise these first
-
A semiconductor supercycle is a multi-year period of investment and growth driven by a fundamental technology shift.
-
Earlier ones were driven by PCs in the 1990s and smartphones in the 2010s.
-
High-bandwidth memory stacks layers of working memory close to the processor so that data moves faster.
-
SK Hynix, Samsung and Micron are the three main HBM producers.
-
Microsoft, Amazon, Google and Meta plan to spend nearly $635 billion on AI infrastructure in 2026.
-
ISM 1.0 approved 12 semiconductor projects.
-
The India Semiconductor Mission sits under the Ministry of Electronics and Information Technology.
-
ISM 2.0 was launched in February 2026 with support for packaging and for chiplet R&D.
-
A fabless company designs and sells chips but outsources their manufacture to foundries.
Connect the dots for your UPSC preparation.
Standard news covers the event. Log in to read our comprehensive analysis and uncover the hidden constitutional, structural, and ethical dimensions of this topic:
How the memory wall, HBM stacking and 2.5D/3D packaging work and why packaging has become a key constraint in AI hardware.
Why chiplets give India a cheaper entry point than leading-edge fabs and what interconnect standards mean for that bet.
What is working and what is not across ISM 1.0 and 2.0, including how much of the design value India actually captures.
A short-term and long-term way forward so India captures more of the supercycle's value, not just a place in the supply chain.
Included in this analysis
Join thousands of aspirants analyzing the news deeply.
Unlock Premium — Rs.699 AnnuallyDon't have an account? Sign up for free