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AI to Drive $150 Billion Manufacturing Boost in India by 2030

CIO Insider Team | Wednesday, 6 May, 2026
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India’s manufacturing sector has entered a decisive phase where Industrial AI has moved beyond experimental pilots into scaled, shopfloor-level deployment. A new report by YourNest Venture Capital, in collaboration with Praxis Global Alliance, reveals that while 90percent of Indian manufacturing enterprises are already experimenting with AI, capital investment is only beginning to catch up.

The report positions Industrial AI as one of the most under-penetrated yet high-potential opportunities in India’s DeepTech ecosystem, with funding projected to grow ten-fold to $1.5 billion by 2030.

The rapid transition is being driven by a "Productivity Stack" effect, where AI delivers measurable, bottom-line impact across the entire manufacturing value chain. Rather than isolated gains, the report identifies a structural uplift in asset utilization and cost competitiveness:

• Asset Optimization: Reductions of 30–50percent in unplanned downtime.
• Operational Efficiency: Decreases of 10–40percent in conversion costs.
• Output Quality: Yield improvements of 5–15percent and throughput increases of up to 30percent.

Beyond individual factory efficiency, the report introduces the “Output Uplift” lens, viewing Industrial AI as a macro-economic catalyst. By optimizing existing assets, Industrial AI is effectively unlocking incremental manufacturing capacity equivalent to ~$150 billion in output by 2030 without the need for proportional physical expansion or heavy greenfield capex. This makes Industrial AI a critical enabler of India’s self-reliance and global supply chain resilience.

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While funding currently stands at a modest $150 million (2024), the report highlights a deepening of capital commitment. Average deal sizes have increased nearly fourfold to approximately $8 million between 2021 and 2025, signaling a shift toward conviction-led, scale-oriented investments.

Sunil K Goyal, Managing Director & Fund Manager, YourNest Venture Capital says, "In India, enterprise adoption of industrial AI has significantly outpaced capital deployment at this pivotal moment. The end-customer is sending out a signal that is being picked by startups who are developing powerful products to make shopfloors more efficient and profitable. We ourselves are seeing increased traction with our early bets in Industrial AI where quantifiable ROI, is lowering downtime, increasing throughput, and optimizing costs. In spite of this, financing is still disproportionately low given the magnitude of the potential. This gap makes it attractive for far-sighted investors to get involved now in creating IP-led, high-impact DeepTech businesses. At YourNest, our focus is on funding globally competitive Industrial AI leaders from India in our next fund.”

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Industrial AI is emerging as a high-Return on Capital Employed (ROCE) lever for the sector. With payback cycles as short as 12–18 months, the business case for scaled adoption has become undeniable for both enterprise CFOs and institutional investors

Ram Soni, Partner, NextGen Industrials, Praxis Global Alliance says, “India’s manufacturing sector is entering a decisive decade. The factories that win will be those that move beyond pilots embedding AI as a shopfloor-first capability with clear, measurable impact on OEE, downtime, yield, and energy. This report captures the ground truth of where that transformation stands today: what is working, what is not, and what manufacturers, founders, and investors must do next to unlock the full potential of intelligent manufacturing in India.”

Industrial AI is emerging as a high-Return on Capital Employed (ROCE) lever for the sector. With payback cycles as short as 12–18 months, the business case for scaled adoption has become undeniable for both enterprise CFOs and institutional investors.

Also Read: From Silos to Synergy: Building the Future With Agentic AI

Unlike traditional software-as-a-service (SaaS), Industrial AI solutions are deeply embedded within physical manufacturing processes. This integration creates higher entry barriers and stronger defensibility. While challenges like legacy system integration and data readiness persist, they are being aggressively addressed as part of broader digital transformation efforts.



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