Indian enterprises are adopting artificial intelligence at a faster pace than global peers and are already reporting tangible business outcomes, but growing data infrastructure complexity and security pressures risk slowing further progress, according to a new study by Hitachi Vantara.
The findings are part of the 2025 State of Data Infrastructure Report, based on a global survey of 1,244 business and IT leaders across 15 countries, including 104 respondents from India. The report suggests that while India is ahead of global benchmarks in AI investment and return on investment (ROI), readiness gaps in infrastructure maturity could limit long-term scalability.
Strong AI momentum in Indian enterprises
Key findings from the report indicate that 89% of Indian organisations have either widely adopted AI or made it critical to business operations, compared with 69% globally. Nearly two-thirds (63%) of Indian respondents said they are already achieving strong or established ROI from AI initiatives, signalling a shift from experimentation to enterprise-scale deployment.
Overall, 75% of Indian organisations reported successful AI outcomes, with no respondents indicating outright failure. The most common use cases driving value include workflow automation, data-driven insights and improved productivity and decision-making.
Infrastructure complexity and data growth pressures
The report highlights a growing operational challenge. 87% of Indian enterprises said their data infrastructure complexity is increasing rapidly or faster, exceeding the global figure of 80%.
AI investment in India is expected to grow 75.6% over the next two years, compared with a global projection of 70.3%, while data storage requirements are forecast to rise by 73.9%, again above the global average. Around 40% of Indian organisations now manage between 50 and 200 petabytes of data—a scale at which infrastructure fragility and operational strain become more pronounced.
The survey also found that Indian enterprises are operating across increasingly fragmented environments. Nearly half of store operational data is in public cloud platforms, with even higher usage for general business data, creating challenges around governance, visibility and control as AI workloads expand.
Security and governance take centre stage
Data security emerged as the leading concern, with 67% of Indian respondents citing it as a primary challenge in AI implementation. In response, Indian organisations appear to be strengthening leadership alignment and governance structures more aggressively than global peers:
- 81% report clearly defined executive AI visions
- 79% have dedicated AI or machine learning teams
- 77% have defined KPIs and business outcomes for AI initiatives
Indian enterprises also reported higher maturity in operational practices such as MLOps, governance models and AI performance monitoring.
A widening AI readiness divide
Despite strong adoption, the report points to a widening readiness gap. While 55% of Indian organisations have reached managed or optimised stages of data infrastructure maturity, the remaining 45% continue to operate on less mature foundations, making AI initiatives harder to scale and more resource-intensive.
Only 32% of organisations reported having predictive, automated and cost-efficient infrastructure scaling in place, limiting their ability to sustain AI-driven ROI as data volumes grow.
Talent shortages drive partner dependence.
Skills availability is another constraint. More than half of Indian respondents cited difficulty in hiring skilled AI and data professionals. As a result, 76% of organisations said they rely on external partners or outsourced expertise for AI and data initiatives—higher than the global average.
The report concludes that while India is well positioned in the global AI race, sustained success will depend on addressing infrastructure complexity, security risks and talent shortages through early investment in automation, governance and modern data foundations.