The data journey A typical SME’s data flows include five datasets that can help address its challenges in cashflow optimization, inventory management, workforce retention, customer engagement and supply-chain efficiency. They are: 1. Financial data such as revenues, costs, receivables, tax filings and credit histories 2. Operational data such as inventory levels, stock- keeping unit (SKU) movements, maintenance logs and production schedules3. Customer insights from order histories, payment cycles, customer feedback and customer relationship management (CRM) records 4. Supply data such as supplier details, delivery schedules and tracking data 5. Environmental data including energy consumption, waste levels and water usage Undertaking the data journey is essential if SMEs are to unlock AI’s potential. By shifting from fragmented manual processes to real-time systems, SMEs can address operational challenges with AI. Data journey – from manual processes to real-time systems TABLE 2 Phase Data sources Data quality How AI can be used Outcomes/impact 0Ledgers, manual logs, physical records (e.g. energy bills, handwritten logs)Data is unstructured, delayed and prone to errorsRetrospective analysis to identify trends from historical dataManual processes lead to slow, reactive decision- making with limited scope for optimization 1Spreadsheets, Tally, Zoho, basic ERP and CRM systemsData is structured but lacks real-time updates and integrationBasic trend identification and automated reportingImproved documentation reduces errors, but decisions remain delayed and operational gaps persist 2Application programming interfaces (APIs), IIoT sensors, QR code-enabled tools, cloud platformsData becomes real- time, centralized and interconnectedPredictive analytics enables proactive planningProactive decisions improve efficiency and reduce costs (e.g. predictive maintenance and inventory control) 3Fully integrated systems combining real-time data and AI toolsData is continuous, real- time and aligned across functionsAutonomous decision- making through prescriptive analyticsFully automated workflows maximize uptime, resource use and customer satisfaction Source: World Economic Forum 3 The AI solutions accessibility challenge SME organizations in India typically operate with low margins, limited financial resources and without a digitally skilled workforce. For AI adoption to scale in SMEs, these organizations need access to affordable, easy-to-use and easy-to-integrate solutions. Additionally, since these organizations are new to the AI transformation journey, lack of funding and AI infrastructure are other major barriers to adoption. These challenges need to be addressed by creating an enabling ecosystem for scaling AI adoption at SMEs. One major challenge regarding accessibility is the lack of AI solutions and testing environments that focus specifically on SMEs and particular SME sectors. Most AI solutions are designed for large enterprises and require complex infrastructure, a high volume of structured data and significant investment. SMEs in India still rely on legacy systems, spreadsheets and basic ERP tools that do not integrate well with existing AI solutions. Additionally, SMEs lack the resources required to test AI applications before full-scale implementation. AI solutions need to be built specifically with SMEs in mind, offering plug-and-play tools and seamless integration with legacy systems. SMEs in India operate with limited resources – both in terms of infrastructure and finance. AI solutions require computational resources that most SMEs cannot afford due to financial and infrastructural limitations. They lack access to cloud platforms, as they are expensive, and are unable to invest in hardware infrastructure. In the absence of structured funding mechanisms that specifically cater to funding for AI adoption by SMEs, adoption becomes a real challenge. SMEs need access to affordable, easy-to-use and easy-to-integrate AI solutions Transforming Small Businesses: An AI Playbook for India’s SMEs 21

Transforming Small Businesses 2025