AI integration expected to contribute up to USD 150 billion to manufacturing sector MSMEs by 2035: Report

Mar 08, 2026

New Delhi [India], March 8 : Artificial Intelligence (AI) could contribute between USD 135.6 billion and USD 149.9 billion to the growth of Micro, Small, and Medium Enterprises (MSMEs) in the manufacturing sector as early as 2035. This projection, according to a PwC report titled "Unlocking the AI Edge for MSMEs," remains contingent on these enterprises accounting for 50 per cent of the nation's manufacturing value added.
The report indicates that MSMEs stand to unlock growth opportunities in the range of USD 3.13-3.21 trillion by 2047. The way forward for this is if India increases the manufacturing share of GDP to 25 per cent and MSMEs raise their contribution to manufacturing gross value added (GVA) from 35.4 per cent in FY 2023-24 to 50 per cent.
Achieving this "exponential 19x leap in value creation" requires MSMEs to adopt AI on shop floors and leverage the technology to become active partners across global value chains.
Beyond direct production, a significant demand-side opportunity exists for MSMEs to supply non-technical manufacturing products to AI infrastructure and chip manufacturers. The report identifies a market for "harnesses, chambers, cooling equipment, and other non-technical manufacturing products" valued between USD 100 billion and USD 150 billion.
With AI expected to contribute USD 1.7 trillion to the overall economy by 2035, the investment required for AI infrastructure is estimated at USD 500 billion.
The report notes that "non-tech-intensive capital goods account for 20-30% of capex on such projects," which is a sector where MSMEs maintain an active presence. By reducing capability barriers across design, quality, and decision-making, AI allows these firms to "leapfrog structural and operational constraints" and "escape the low-productivity trap."
Technological integration enables MSMEs to reposition themselves as "competitive value creators rather than cost-based suppliers." Specific applications include predictive maintenance, vision-led quality control, and intelligent inventory management. Furthermore, AI combined with local language models simplifies interfaces and reduces the need for technical expertise.
The report defines AI's role through three functions: a "Scaler" that decreases processing times, an "Enricher" that augments human decision-making, and a "Reinventor" that transforms how value is captured.
To manage this transition, the study proposes a "3A2I framework" built around "access, acceptance, assimilation, implementation, and institutionalisation" to help firms translate adoption into measurable value.

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