Transforming Small Businesses 2025

A detailed look at three AI use cases for India’s SMEs From the 10 use case categories described above, the report team analysed six AI applications in detail. Three of these are described below, while three are presented in the section on “AI agents – a new frontier in AI technology”, where the team looked at how these applications can be enabled via AI agents. While all of these use cases represent opportunities for value creation, their implementation must be adapted to local contexts and specific environments, and each SME must prioritize their use after considering specific factors such as its technological readiness, digital infrastructure, workforce capabilities and strategic objectives.1 Predictive maintenance and supply-chain efficiency The context India’s manufacturing SMEs usually rely on break–fix maintenance, addressing equipment issues only after failures occur. This results in unplanned downtimes and maintenance costs that can be significantly higher than planned maintenance schedules. It also requires investment in a large spare-parts inventory, which eats up limited working capital. By contrast, AI and machine learning (ML)-driven predictive maintenance offers solutions through IoT sensor data analysis, which enables failure forecasting and an optimized maintenance schedule. Early implementations show promising results, with 20–40% reductions in unplanned downtime and a 10% decrease in equipment ownership costs.25 For Indian SMEs that work with global supply chains, predictive maintenance enhances operational reliability, reduces risks and strengthens their competitive positioning by boosting efficiency. Early implementations of AI-based predictive maintenance show promising results, with 20–40% reduction in unplanned downtimeIndicative use case prioritization for the Coimbatore textile cluster BOX 2 To illustrate the scoring system, the research team analysed the different use case categories previously identified and scored them on the parameters of impact and feasibility listed above from the perspective of the textile cluster in Coimbatore. After arriving at a weighted average score each for impact and feasibility, these use cases were mapped as shown in below. Each identified use case is evaluated on the sub-parameters for impact and feasibility …… and a weighted average is taken to map the use cases on the impact–feasibility matrix Impact Feasibility Supply-chain efficiencyUse case categoryBusiness valueStrategic alignmentPeople impactData demandCost to deployOperational readiness Workforce and talent Quality Safety Customer experience Sustainability Financial efficiency Regulatory compliance Credit access Virtual prototypingFeasibilityImpactHigh Medium Low High Medium LowVirtual prototypingSustainabilitySupply-chain efficiency Financial efficiency QualitySafety Credit accessRegulatory compliance Customer experience Workforce and talent Investable bets Ideal AI pilots Quick wins Backburner53 4 4555 2 232 4 5435 3 145 3 4234 5 344 2 5141 3 543 2 5341 2 535 3 5 1 2 1 23 5343 3 4 Note: 1 = least favourable; 5 = most favourable. Source: World Economic Forum. Transforming Small Businesses: An AI Playbook for India’s SMEs 27