How AI is helping India move up the global chip design value chain
By Suresh Babu Katta, Founder & Chief Executive Officer, Nanopowered Technologies
Semiconductors have become strategic assets, underpinning AI, mobility, telecommunications, healthcare, and defence. Nations across the world are investing heavily in building out their semiconductor ecosystems, recognising that chips now sit at the centre of both economic competitiveness and national security.
For years, discussions around India’s semiconductor ambitions have centred on fabrication plants. Every major announcement measured in billions of dollars invested, factories commissioned, and manufacturing capacity created has been for fabrication plants. These investments matter. But they risk overshadowing a more significant transformation already underway.
Semiconductor leadership will no longer be decided only inside fabrication facilities. Increasingly, it will be determined long before silicon reaches a wafer, during chip design. For India, the opportunity isn’t confined to manufacturing; it lies in moving higher up the value chain through chip design, and artificial intelligence is emerging as the biggest accelerator of that transition.
The real bottleneck is no longer manufacturing
Designing an advanced semiconductor is one of the most complex engineering challenges in existence. Modern chips contain tens of billions of transistors, and engineers must optimize thousands of interconnected variables at once, which includes balancing performance, power consumption, thermal efficiency, manufacturability, and cost.
Every design iteration traditionally requires weeks of simulation, verification, and optimization. Small errors caught late in the cycle can delay products by months and add millions of dollars in engineering costs. As chips grow more specialized this complexity is compounding. Traditional design methodologies are reaching their limits.
AI is changing the economics of chip design
Artificial intelligence is becoming a co-engineer rather than just another tool in the workflow. Across the design process, AI helps engineers automate repetitive optimization tasks, catch bottlenecks earlier, and explore millions of design permutations that would be impossible to test manually.
Where engineers once tested hundreds of layouts by hand, AI systems now evaluate thousands within hours. Where timing violations or power inefficiencies once surfaced only after weeks of work, they can now be caught at earlier design stages. And where floorplan or routing decisions once relied purely on experience, AI can learn from prior designs and recommend better configurations.
Much of this is being driven by AI-assisted Electronic Design Automation (EDA): automated layout generation, faster design-space exploration, and fewer engineering iterations per chip. These capabilities are compressing timelines that used to stretch across months into a matter of weeks.
The result isn’t just faster chips, it’s faster innovation. Companies are reaching tape-out sooner, cutting engineering costs, and accelerating time-to-market, while freeing experienced designers to focus on architectural innovation instead of repetitive optimization.
Today, nearly one in every five chip designers globally is based in India, and global semiconductor companies have relied on Indian engineering teams for decades to design processors, communication chips, automotive electronics, and embedded systems. This is backed by decades of expertise in embedded systems, VLSI design, and engineering services, along with a growing presence of global semiconductor R&D centres on Indian soil.
But much of that work has historically sat within outsourced development models: Indian engineers helped build the products but rarely owned the intellectual property behind them. India’s traditional strength has been engineering execution, the next challenge is creating more indigenous intellectual property, building genuine design capabilities, and compressing innovation cycles.
AI has the potential to close that gap. As it automates large portions of verification, layout optimization, and design exploration, the barriers to creating original semiconductor IP fall significantly, freeing engineers to contribute more to architecture, system design, and innovation rather than routine execution. The competitive edge shifts away from simply having the largest engineering workforce and toward having the fastest innovation ecosystem. That points to a broader shift already taking shape: from service provider to technology creator, with greater ownership of complex semiconductor programmes. India is well positioned to benefit from exactly that shift.
The transition is already underway
Indian startups are developing AI processors, edge AI chips, and specialized semiconductor IP for applications spanning industrial automation, surveillance, robotics, and telecommunications. Global semiconductor companies are expanding advanced design centres across Bengaluru, Hyderabad, and Noida to work on cutting-edge nodes.
Government initiatives including the Design Linked Incentive (DLI) Scheme, the Chips to Startup (C2S) programme, and the India Semiconductor Mission are building an ecosystem where startups get access to EDA tools, funding, and silicon prototyping once available only to large multinationals.
The conversation is shifting from “Can India design chips?” to “Can India own the next generation of chip architectures?” That’s a far more consequential question.
Fabs alone won’t create semiconductor leadership
Fabrication is essential, but it is only one part of the semiconductor value chain. India must continue investing in advanced manufacturing, packaging, testing, and resilient supply chains while simultaneously building indigenous chip design capabilities and reusable semiconductor IP.
Without a strong pipeline of India-owned, patented, high-volume semiconductor products, foundries will remain dependent on external customers for wafer demand. Given the enormous capital investment in fabrication facilities and the need for wafer processing equipment to operate at high utilization (often 24×7) to remain economically viable, sustained production volumes are critical. Indigenous, production-scale chip platforms are therefore indispensable not only for technological self-reliance but also for ensuring the long-term commercial viability and profitability of India’s semiconductor manufacturing ecosystem. Otherwise, fabs risk becoming merely manufacturing infrastructure rather than engines of innovation, IP creation, and sustainable economic growth.
True value lies in intellectual property, architecture, and design and AI is making these capabilities more accessible than ever. The countries that combine world-class engineering talent with AI-enabled design workflows will define the next era of semiconductor innovation.
Every major technology transition rewards those who recognize where value is moving. For decades, semiconductor leadership was measured by manufacturing capacity. Tomorrow, it will be measured by the ability to design better chips, faster.
India already has one of the world’s largest pools of semiconductor talent. Artificial intelligence gives that talent something it has never had before: the ability to innovate at unprecedented speed.
The real opportunity is to move decisively up from designing for others to designing what the world builds next.