# India’s AI Chip Ambitions Face Reality at SEMICON India 2026 > Source: > Published: 2026-09-20 13:08:16+00:00 **September 20, 2026, (Inside AI) —** India's semiconductor ambitions collided with the AI-driven global chip boom this week as **SEMICON India** drew nearly **600 companies** from **52 countries** to New Delhi. Prime Minister **Narendra Modi** inaugurated the event, declaring that "India's semiconductor ecosystem is expanding rapidly." The conference, organized under the **India Semiconductor Mission (ISM)** and the **Ministry of Electronics and Information Technology (MeitY)**, highlighted a stark reality: India is participating in the AI chip supercycle largely as a consumer, not a producer. The global semiconductor industry is in the midst of a supercycle, a multi-year surge in demand driven by artificial intelligence and the data centers that power it. Unlike previous booms tied to PCs in the 1990s or smartphones in the 2010s, this cycle is reshaping the very structure of chip demand, shifting it from consumer electronics to business-to-business contracts. For India, the opportunity is immense but so are the gaps. ## India's Missing Piece: Wafer Fabs At the heart of the AI boom are **graphics processing units (GPUs)** and **high-bandwidth memory (HBM)** chips. GPUs handle the massive calculations needed to train and run AI models, while HBM stacks memory layers close to the processor to move data at high speeds. The HBM market is dominated by just three players: South Korea's **SK Hynix** and **Samsung**, and **Micron** in the United States. According to Micron, producing HBM requires three times the manufacturing capacity of standard memory because the chips are physically larger and involve stacking up to **16 layers**, where a single defect can ruin the entire stack. India has no large-scale wafer fabrication plant actively producing chips. Under ISM 1.0, the government approved **12 semiconductor projects**, but most focus on assembly, testing, and packaging. Micron's Sanand facility in Gujarat will process imported wafers, and Sahasra Semiconductors will package NAND flash storage. These projects place India at the later stages of memory chip production, while wafer manufacturing remains elsewhere. **Read:** **SK Hynix Breaks Ground on $4 Billion Indiana AI Chip Packaging Facility** This means India experiences the AI chip boom mainly through higher import costs and tighter supplies. In July, a parliamentary reply noted that demand from AI servers and data centers was tightening memory supplies and raising prices. The effects are also visible in capital markets: some foreign investment withdrawals from India in 2026 have been linked to growing interest in the semiconductor-heavy markets of Taiwan and South Korea. ## Packaging And Chiplets: India's Entry Point ISM 2.0 aims to build on the existing base with a packaging scheme that offers financial support for capital expenditure. The scheme also covers other manufacturing stages that help connect processors and memory within AI systems. Another scheme will support R&D in chiplet technologies, which combine several smaller, specialized chips to lower costs and work around the physical limits of traditional silicon. The **NITI Aayog** semiconductor roadmap report recommends establishing pilot lines for chiplets and HBM-class integration, which would combine advanced processors and memory via packaging techniques. Chip design offers another entry point, as nearly a fifth of the global chip workforce is based in India. Under the design-linked incentive scheme, startup **Netrasemi** is developing edge-AI processors for cameras, drones, and robots, performing AI computations on the device instead of sending data to the cloud. Germany's **Infineon** recently acquired Bangalore-based fabless company **C2i**, which designs AI power controllers, illustrating another part of an emerging value chain. These moves suggest India could carve out a niche in design and advanced packaging, even without leading-edge fabs. The AI infrastructure spending boom is concentrated among a small group of cloud and AI companies. According to S&P Global data, **Microsoft**, **Amazon**, **Google**, and **Meta** have planned to spend nearly **$635 billion** on AI infrastructure in 2026 alone. Memory chipmakers are entering long-term take-or-pay agreements, where customers must buy agreed chips regardless of demand or pay penalties. In June, Micron reportedly signed **16 such agreements** covering roughly 2026 to 2030. These contracts may make demand more predictable, but the industry's fortunes ultimately depend on the revenue AI services generate relative to the sizable investments. The commercial relationships are also interconnected: [chip designer **Nvidia**](https://insideai.news/news/ai-hardware-infrastructure/nvidia-faces-growth-test-as-rubin-debut-meets-ai-financing-scrutiny/8691/) has taken a **7% stake** in AI cloud company **CoreWeave** and agreed to buy **$6.3 billion** worth of services from it. In turn, CoreWeave relies on Nvidia chips. **OpenAI** has agreed to purchase AMD chips and is poised to become one of AMD's largest shareholders. Beyond data centers, robotics and autonomous vehicles are poised to increase demand. According to Micron's estimates, such vehicles contain more than five times the memory and storage of an average car, while humanoid robots will require 10 times more than those vehicles. India's focus on packaging and design could position it to supply components for these emerging sectors, but competition is fierce. As SEMICON India wraps up, the message is clear: the AI chip supercycle is reshaping global supply chains, and India must accelerate its efforts to move beyond assembly and into higher-value manufacturing. The window of opportunity is open, but closing fast.