Unlocking economic value: AI as a growth engine for MSMEs AI adoption in MSMEs has the potential to unlock $490–685 billion in economic value. This represents growth of around 45–62% for the sector, which currently contributes about $1.1 trillion to GDP . However, while this represents the potential, the actual value realized will depend on the level of adoption across the ecosystem as well as the depth of AI implementation. With time, the level of adoption and depth will increase, leading to a convergence of potential and realized value. This value can be measured along three levers: 1. Productivity enhancement: AI-driven automation, predictive analytics, process optimization and market insights can boost the overall productivity of the MSME sector, thereby enabling MSMEs to generate a higher revenue per unit input. Initial pilots of AI in Indian MSMEs have shown a productivity increase of 15–20%.7 Given the current GDP contribution of the MSME sector ($1.1 trillion), this represents a value increase of $160–215 billion. 2. Cost reduction: AI can drive efficiencies in operations, logistics, supply-chain management and resource management, thereby reducing costs for organizations. Pilots of AI implementation in Indian MSMEs have shown a 20–30% reduction in costs as a direct result of AI implementation.8 MSMEs in India currently operate at an overall earnings before interest, taxes, depreciation and amortization (EBITDA) margin of 6–6.5%,9 or, in other words, have operational costs of 93.5–94% of revenue. Given these low margins, such enterprises can benefit greatly from cost reduction and margin expansion. AI implementation has the potential to unlock $200–300 billion in cost savings in the MSME ecosystem. 3. Financial inclusion: MSMEs in India lag significantly behind other countries such as China and the United States in terms of formal credit penetration. Only 19% of the total MSME credit demand in India is met through formal credit sources, leaving behind a massive credit gap of $530 billion.10 Thus, MSMEs have to rely on informal lenders to meet their credit needs. These informal lenders process loans without asking for extensive documentation but charge an interest rate typically 12–16% higher than that charged by formal lenders.11 AI-driven data capture, documentation and credit assessment models can help bridge this credit gap and enable formal credit access for several MSMEs, thus unlocking $130–170 billion in economic value (assuming an incremental capital output ration [ICOR] of 2 for the MSME sector).AI as a business enabler: Impact for MSME entrepreneurs Beyond a macroeconomic impact, AI adoption by Indian MSMEs can translate into direct measurable advantages for the MSME entrepreneur. It is important to identify this benefit from the perspective of MSME entrepreneurs/owners. As one MSME owner pointed out during consultations, they want to see the value that AI can generate for them before making any investment in the technology. AI can improve metrics in three areas: productivity enhancement, cost reduction and financial inclusion. This improvement can help MSME entrepreneurs drive revenue growth, improve margins and expand business operations. AI adoption by MSMEs can significantly increase shopfloor productivity, translating to greater revenue generation for the MSME entrepreneur. Results from across the World Economic Forum’s Global Lighthouse Network12 suggest that labour productivity can increase by 30–40%, while overall equipment effectiveness can increase by 10–30% through AI implementation. Additionally, AI can also help reduce lead times by 30–40% and increase on- time delivery by about 10–20%. While the Lighthouse Network includes larger enterprises, MSMEs can realize similar benefits through AI adoption. Studies also show that AI has the potential to reduce product cost by up to 32%, operating cost by 24% and defect rates by up to 99%. The use of AI can also drastically reduce inventory, thus leading to further cost savings and freeing up working capital. Furthermore, AI-driven sustainability initiatives can lead to waste reduction of up to 64% and increase energy efficiency by up to 59%. Thus, the adoption of AI can improve margins and drive a measurable impact on individual MSME businesses. The use of AI by lenders and MSMEs can also drive financial inclusion and enable formal credit for many unserved MSMEs. Currently, a significant chunk of MSMEs lack access to formal credit because they do not have the extensive documentation required for credit appraisal. AI can enable alternative credit assessment models that can better measure the risk of enterprises using alternative sources of data. The interest rate charged by informal lenders in India to MSMEs can be 12–16% higher compared to formal credit institutions. Thus, AI- driven credit assessment can lead to a significant reduction in finance costs for MSMEs. In addition, while traditional loan processing can take weeks to months for MSMEs, AI-driven models can reduce this time to a few hours. AI adoption in MSMEs has the potential to unlock $490–685 billion in economic value. Transforming Small Businesses: An AI Playbook for India’s SMEs 9

Transforming Small Businesses 2025