Context:

• Technology is increasingly becoming the foundation of economic growth and national power.
• The global AI revolution has intensified competition in semiconductors, making technological self-reliance a strategic necessity.
• India's semiconductor and AI policies over the next few years will determine its position in the global technology value chain.

Global Semiconductor Race and India's Strategic Imperative:

• Semiconductors are critical to economic competitiveness, national security and technological sovereignty. Major economies are investing heavily to secure their position.
• For example,
  • Taiwan: Dominates advanced semiconductor fabrication and is indispensable to global supply chains.
  • South Korea: Samsung and SK Hynix have benefited from the AI-driven demand for advanced chips.
  • China: Has invested an estimated $150 billion in semiconductor self-sufficiency since 2015.
  • United States: The CHIPS Act provided $53 billion in direct subsidies, catalysing substantial private investment.
• India possesses two critical advantages - demographic scale and intellectual capital, supported by a large pool of engineers and scientists.
• However, historical underinvestment in technological sovereignty has left it vulnerable to external technology restrictions.
• The US restrictions on access to certain AI models highlight how technology denial can become an instrument of geopolitical influence.
• India must therefore develop indigenous capabilities to safeguard its strategic autonomy.

India's Semiconductor Initiatives - Progress and Limitations:

• The government has introduced several initiatives to strengthen domestic capabilities.
• For instance,
  • India Semiconductor Mission (ISM):
    • Promotes domestic semiconductor manufacturing and ecosystem development.
    • At SEMICON India 2026, the government reported 12 approved semiconductor manufacturing units, with committed investments of ₹1.64 lakh crore and five facilities in production.
    • ISM 2.0 envisages an additional ₹1.275 lakh crore.
  • Design Linked Incentive (DLI) Scheme: Supports semiconductor design and indigenous intellectual property (IP).
  • IndiaAI Mission: Strengthens India's AI ecosystem and access to computing infrastructure.
• Structural limitation:
  • Nine of the 12 approved units focus on conventional Assembly, Testing, Marking and Packaging (ATMP) or Outsourced Semiconductor Assembly and Test (OSAT).
  • These activities generally offer lower margins and limited technological differentiation compared with advanced packaging and chip design.
• Thus, investment commitments alone cannot establish technological leadership. India must move towards higher-value segments of the semiconductor industry.

From Electronics Assembly to Advanced Semiconductor Capabilities:

• India's electronics Production Linked Incentive (PLI) scheme successfully leveraged the China+1 strategy.
• It encouraged companies such as Apple and Samsung to diversify their manufacturing bases. India now assembles approximately 25–28% of iPhones globally.
• However, semiconductors present a different challenge. Unlike electronics assembly, the semiconductor industry is undergoing an architectural transformation driven by AI.
• The growing demand for AI computing has increased the importance of chip design, intellectual property (IP) and advanced packaging.
• Advanced packaging technologies, such as CoWoS (Chip-on-Wafer-on-Substrate), enable the integration of GPUs and high-bandwidth memory. They offer greater value addition than conventional packaging.
• India must therefore shift its focus towards advanced packaging, semiconductor research, indigenous design IP and fabrication capabilities.

Strengthening Semiconductor Research and Innovation:

• India lacks a dedicated semiconductor research institution with the depth required to develop advanced process technologies and indigenous IP.
• The proposed National Semiconductor Research Institute, envisaged under ISM 1.0, should be established without further delay.
• It should be jointly funded by the government and industry and focus on -
  • Developing indigenous semiconductor process technologies.
  • Promoting advanced chip design and intellectual property.
  • Building a skilled semiconductor workforce.
  • Strengthening collaboration between academia, industry and research institutions.
• Such an institution would bridge the gap between academic research and commercial semiconductor manufacturing.

India's Opportunity in AI Inference Chips:

• The AI semiconductor market is increasingly divided into two segments -
• AI training:
  • Training involves developing AI models using massive computing infrastructure.
  • This market is concentrated around NVIDIA's CUDA ecosystem and specialised chips developed by major cloud companies, making entry difficult for new players.
• AI inference:
  • Inference involves deploying trained AI models to generate responses and perform tasks.
  • It offers significant opportunities because computing requirements vary across cloud services, smartphones, defence, agriculture and industrial applications.
• Unlike AI training, inference does not require a single dominant architecture. This creates opportunities for specialised, application-specific chips.
• India has several advantages -
  • Approximately 1.25 lakh semiconductor design engineers.
  • The Digital India RISC-V (DIR-V) program, based on open-source RISC-V architecture, which can reduce dependence on proprietary instruction-set licensing.
  • Growing demand from defence, 5G infrastructure, agriculture and industrial applications.
  • A large domestic market and the IndiaAI Mission's sovereign computing initiatives.
• Developing indigenous AI inference chips could help Indian companies capture greater value in the semiconductor ecosystem.

Way Forward:

• India's primary challenge is the shortage of capital and institutional support for taking indigenous chip designs from prototypes to commercial production.
• The following measures are essential -
  • Expand the DLI Scheme: Provide sustained financial support to domestic fabless semiconductor companies, including commercialisation and tape-out stages.
  • Establish a Chip Design Commercialisation Fund: Approx. ₹1,000 crore fund, modelled on the National Investment and Infrastructure Fund (NIIF), to support Indian chip startups.

Conclusion:

• The AI-driven semiconductor supercycle offers an opportunity to strengthen India's economic competitiveness and strategic autonomy.
• A focused national strategy is essential for India to become a significant player in the global technology ecosystem.