Artificial intelligence-enabled quality inspection to detect weaving or dying defects in real time in textiles, or predictive maintenance tools reducing machine downtime, or identifying the source of a specific solvent in a contaminated cough syrup, or real-time measurement using AI to track emissions, energy intensity rather than retrospectively — these were some of the case scenarios policymakers cited at the India AI Impact Summit on Tuesday.
These AI-linked interventions may not just help scale up manufacturing but also improve quality and competitiveness of the country’s industrial sector going ahead.
In this transition towards AI, the officials said the key role will need to be played by micro, small and medium enterprises (MSMEs) — over 76 million in number, of which about one-fifth are in manufacturing.
“While large enterprises typically have ways to finance this transition and are able to make the necessary investments, smaller enterprises and enterprises in traditional sectors like textiles, may or may not necessarily be in the position to make the kind of investments which are needed to support this (transition),” said S Krishnan, Secretary, Ministry of Electronics and Information Technology (MeitY).
The officials launched a study on AI adoption and impact on manufacturing MSMEs by Athena Infonomics in partnership with National Institute for Smart Government and line ministries of MSMEs, textiles, and pharmaceuticals.
MSME Secretary SCL Das said the AI-powered transformation has to be essentially led by industry, especially MSMEs that contribute hugely to employment and the economy.
But it does require several support systems involving public support and public investment, he said.
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“It’s a partnership where primarily the solutions will come from the industry. At the same time, the government would have to do its bit in terms of tweaking the policy design in terms of providing resources where private sector resources would not automatically come,” he said.
Emphasising that India’s battle for AI will be won or lost on the factory shop floor, Rohit Kansal, Additional Secretary, Ministry of Textiles said the country’s long-term economic shift cannot solely be determined by digital native businesses and will eventually be decided by the use of AI to modernise legacy industries like textiles, food processing, leather.
“Productivity improvement in these sectors and MSMEs will matter far more for national income than incremental gains in already digitised sectors,” he said.
He said global buyers increasingly value consistent quality, delivery reliability, and transparent supply chains, and competitiveness no longer depends on labour or wage arbitrage.
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“They demand granular visibility across production networks, and AI-driven measurement networks can allow Indian firms to meet all these standards at lower compliance and verification costs,” he said.
If AI is not adopted as of now, then it is possible that India’s manufacturing sector may lag behind and that’s why to remain competitive and remain market ready, it’s essential to bring solutions, Bhuvnesh Kumar, Chief Executive Officer, NISG said.
“This is an opportunity not only for the MSMEs, but for a large number of startups and AI-solution providers,” he added.
A shelf of AI-based solutions could be offered to MSMEs, which can then be customised by them as per their requirements, Kumar said, adding that some kind of government support may also be offered to MSMEs for AI adoption in the future.
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“We really want the MSMEs to remain competitive and offer the best of the solutions to the market at an affordable price for the consumers. That’s the most important part,” he said.
MSMEs have to adopt some of the basic traceability, data interoperability mechanisms, Kansal said.
Also, for MSMEs, any returns from AI have to be visible and timebound, he said, adding that cluster-level deployment, shared digital infrastructure, and common data standards are important.
“Collective service platforms can help us adopt lower adoption costs and create scale efficiencies. Vendor lock-in has to be discouraged as much as possible,” he said. More importantly, AI has to be seen as productivity-enhancing, not labour displacing, he said, adding that AI adoption in MSMEs will improve, only when quality is improved without impacting jobs.
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