AI is reshaping Indian tech SMEs, but scaling challenges still run deep

While 94% of SMEs view AI as essential for future growth, only 36% pursue it through a long-term strategic lens. The majority remain reactive, responding to immediate client needs or internal efficiency targets. Experts warn that this short-term approach risks capping long-term competitiveness in a global digital economy increasingly driven by automation and intelligent platforms.

Indian technology small and medium enterprises (SMEs) are undergoing a fundamental shift in strategy as they accelerate the adoption of artificial intelligence (AI) and digital services, yet remain constrained by cost pressures, talent shortages, and uncertain returns on investment. This is the key finding from a major new industry study released by Nasscom and UnearthInsight, which analyzed over 3,500 SMEs and conducted primary interviews with more than 30 AI leaders across the country.

The report titled "Transforming India’s Technology SMEs for a Digital Future: Navigating the AI Frontier," estimates that Indian tech SMEs will generate revenues of $17–18 billion in FY25, accounting for 6-7% of the country’s tech sector. These firms, historically focused on IT services and subcontracting, are now moving rapidly into high-value digital engineering, AI-as-a-service, and embedded AI solutions. Despite this shift, 80% of the surveyed SMEs derive less than 15% of their revenues from AI-related services, and most allocate under 10% of their tech budgets to AI investments.

While 94% of SMEs view AI as essential for future growth, only 36% pursue it through a long-term strategic lens. The majority remain reactive, responding to immediate client needs or internal efficiency targets. Experts warn that this short-term approach risks capping long-term competitiveness in a global digital economy increasingly driven by automation and intelligent platforms.

The study identifies several key friction points holding back transformative AI integration. Chief among them are ambiguous return on investment (ROI) frameworks, limited in-house AI talent, fragmented funding models, and weak demand from larger enterprises for SME-developed AI products. Although most SMEs have begun integrating AI into their existing service stacks, only 18% currently offer AI as a standalone product or platform. This reflects a cautious approach to disruption, with incremental improvements preferred over bolder innovation plays.

Digital services, including AI, analytics, and cloud engineering, are growing 1.4 times faster than traditional IT offerings. Between FY23 and FY25, digital revenue share in Indian tech SMEs rose from 36% to 44%, while traditional application development and maintenance dropped from 59% to 54%. This trend is particularly evident in emerging verticals like healthcare, hi-tech, and SaaS, which have seen SMEs increase their market penetration across both domestic and international geographies.

North America remains the largest market for Indian SMEs, accounting for the majority of digital service exports, but there is growing traction in Japan, Southeast Asia, and the Middle East. Domestic opportunities are also expanding in sectors like banking, public utilities, and retail, driven by demand for cloud modernization, low-code platforms, and vernacular AI interfaces.

The report highlights that Indian SMEs now employ over 130,000 digital service professionals, including specialists in cloud, agentic AI, and platform engineering, with an annualized growth rate of 12%. However, the study notes a persistent mismatch between skills and strategic needs. More than 75% of SMEs spend the majority of their AI budgets on human capital, primarily salaries and training, rather than investing in scalable technology platforms, research and development, or proprietary IP.

Scaling is a particularly acute challenge. Most SMEs struggle to move from pilot projects to enterprise-wide deployment due to steep costs, unclear ROI, and integration difficulties with legacy systems. Only 32% maintain dedicated AI budgets; others rely on project-based allocations or combine AI spending within broader IT budgets, resulting in fragmented planning and underfunded execution.

On the operational front, SMEs are increasingly shifting from founder-led sales strategies to structured go-to-market models. Partnerships with cloud giants like Microsoft, AWS, and Salesforce have expanded significantly, particularly in Tier-II cities such as Jaipur, Coimbatore, and Ahmedabad. Direct sales and regional offices are also gaining ground, replacing organic networks with more scalable frameworks.

Nevertheless, market traction for SME-built AI solutions remains limited. Large enterprises, both in India and overseas, continue to favor established players for strategic transformation deals, citing quality assurance and scalability concerns. Without certification mechanisms or standardized evaluation frameworks, many SME innovations remain untested at enterprise scale, stifling commercialization.

The report proposes a multi-phase roadmap to address these systemic challenges. In the short term, it recommends the development of sector-specific AI toolkits, hands-on training programs, and peer mentorship networks to boost implementation confidence. Medium-term priorities include establishing government-backed cloud credits, AI-specific financing schemes, and middleware solutions for legacy system integration. Over the long term, sustained investments in talent development, academic partnerships, and upskilling programs will be critical to ensuring a future-ready SME workforce.

Policy interventions are also called for. Nasscom recommends that government agencies provide tax incentives for AI adoption, create public-private AI innovation labs, and establish standardized frameworks for data governance and model scalability. It also proposes dedicated funding lines for AI infrastructure and a national platform to showcase SME-developed AI solutions to enterprise buyers.

The report's case studies showcase successful SME-led AI deployments across sectors including retail, healthcare, banking, and public administration. Examples range from automated sentiment analysis in fashion e-commerce, to real-time analytics in medical trials, to LLM-powered legal aid platforms. These stories illustrate AI’s tangible value, but also underscore the need for systemic enablers to move from isolated success to widespread impact.

Looking ahead to FY30, Nasscom forecasts a $33–36 billion opportunity for Indian tech SMEs, with digital services comprising 40-44% of total revenue at a compound annual growth rate of 17–19%. To capture this upside, SMEs must transition from exploratory AI use to strategic, outcome-driven deployment. Without this shift, the sector risks falling behind global peers in a rapidly maturing AI economy.