Enterprise AI Adoption In India: Insights From Ranjan Chopra, Team Computers

India's enterprise AI journey is moving from awareness to adoption, with many organizations experimenting and investing in AI technologies. However, the depth of adoption varies greatly among companies. According to an IDC/IndiaAI study, 76% of Indian companies are running GenAI proof of concepts or have investment plans in place, while NASSCOM's AI Adoption Index 2.0 places India's overall AI maturity at 2.47 out of 4.

Despite this broad interest, the evidence suggests that deep, enterprise-wide implementation is still limited. Gartner's 2024 AI Mandates survey indicates that while AI adoption is real, it is less pervasive than often assumed. Among high-maturity organizations, 45% have kept AI initiatives in production for three-plus years, compared to just 20% of low-maturity organizations. This suggests that successful AI adoption requires more than just experimentation; it needs to become a durable, integrated business capability.

GenAI has made experimentation faster and cheaper, allowing teams to test applications in various areas like customer service, software development, marketing, analytics, and productivity. However, moving from successful demos to production systems is far more challenging. Data availability and quality are major barriers, especially for high-maturity firms, with 29% citing data as a top challenge and 48% flagging security threats as top concerns.

Low-maturity organizations often struggle more to find the right use case (37%) than to deploy proven GenAI solutions.

India's financial services sector provides a good example of this challenge. While there is strong interest and experimentation, regulatory requirements, data sensitivity, and explainability needs make the path to production more deliberate. The pattern across industries is similar - pilots multiply quickly, but production-scale adoption lags far behind.

Investment in AI is increasing in India, with IDC forecasting India's AI/GenAI spending (hardware, software, services) could reach approximately $6 billion by 2027. Gartner projects overall IT spending of $176.3 billion in 2026, with AI infrastructure driving data-center growth and CIO priorities. However, spending alone does not guarantee returns.

Investment is increasingly flowing into foundational capabilities - cloud, compute, data platforms, cybersecurity, and integration - rather than standalone tools. The real differentiator is institutional commitment, with 91% of leaders at high-maturity organizations having appointed dedicated AI leaders, compared to just 37% at low-maturity organizations.