Indian enterprises are accelerating AI adoption and realizing business value at a pace that exceeds global benchmarks. However, this rapid progress is increasingly being challenged by rising data infrastructure complexity and heightened security demands, according to a new report from Hitachi Vantara, the data storage, infrastructure, and hybrid cloud management subsidiary of Hitachi Ltd. (TSE: 6501).
The company’s 2025 State of Data Infrastructure Report, released recently is based on a global survey of 1,244 business and IT leaders across 15 countries, including 104 respondents in India. Key findings show that:
- 89% of Indian organizations have either widely adopted AI or made it critical to operations, significantly exceeding the global average (69%).
- Nearly two-thirds (63%) of Indian organizations rate themselves as strong or established (with some gaps) in achieving ROI from AI, above the global benchmark, indicating that India has largely moved beyond pilots into enterprise-scale deployment.
- However, this acceleration comes with mounting pressure: 87% of Indian enterprises say their data infrastructure complexity is increasing rapidly or faster, compared with 80% globally
“Indian enterprises have moved well beyond experimenting with AI and are now focused on delivering measurable business outcomes at scale,” said Hemant Tiwari, Managing Director, Hitachi Vantara, India & SAARC. “What’s becoming clear is that as adoption accelerates, infrastructure complexity is rising just as fast. The organizations that continue to pull ahead will be the ones that modernize their data foundations early, so AI momentum isn’t slowed by fragility, risk, or operational strain.”
Explosive Growth Drives Operational Strain
AI investment in India is projected to increase by 75.6% over the next two years, surpassing the global forecast of 70.3%. Correspondingly, data storage demands are expected to grow 73.9%, compared with 68.9% worldwide. Currently, 40% of Indian organizations manage between 50 and 200 petabytes of data, significantly higher than the global figure of 31%, a range where infrastructure strain becomes particularly pronounced.
This expansion spans increasingly fragmented environments. In India, nearly half (46%) of the organizations surveyed store operational data in public cloud, with even higher usage for general business data. This multi-environment reality creates governance, visibility, and control concerns, that intensify as AI workloads scale.
Security, A Dominant Concern
As AI adoption accelerates, security has become the dominant concern for Indian enterprises. Two-thirds (67%) cite data security as a leading challenge when implementing AI, placing India among the most security-conscious markets globally.
Indian organizations are responding with stronger governance frameworks and leadership alignment than many global peers:
• 81% report executive teams with clearly defined AI visions (71% globally)
• 79% have dedicated AI or machine learning teams (70% globally)
• 77% have defined KPIs and expected business outcomes for AI initiatives (67% globally)
Indian enterprises also lead in operational discipline. 71% rate their MLOps (Machine Learning Operations) capabilities as strong and established versus 63% globally, 63% have advanced governance models versus 49% globally, and 89% monitor AI performance versus 85% globally. Additionally, 54% have sustainability embedded in infrastructure versus 42% globally.
The survey found that 75% of Indian organizations report successful AI outcomes, with virtually no respondents reporting outright failures. The primary use cases driving this value include automating workflows (29%), generating insights (29%), and improving productivity and decision-making (26%). Success drivers include, high-quality data (65%), robust monitoring (61%), employee adoption (61%), and skilled teams (59%).
The AI Readiness Divide: 45% of Organizations Risk Falling Behind
Beneath strong AI adoption and leadership alignment, a clear readiness gap is emerging. While 55% of Indian organizations have reached the managed or optimized data infrastructure maturity stages, the remaining 45% continue to operate with less mature foundations, making AI initiatives more resource-intensive and harder to scale reliably.
The divide becomes more pronounced at the operational level. Only 32% of organizations report having predictive, automated, and cost-efficient infrastructure scaling in place, limiting their ability to sustain AI ROI as data volumes and workloads grow.
“The real bottleneck for AI isn’t the models, it’s when the data backbone lags behind,” said Sanjay Agrawal, CTO, Head Pre-sales, India and SAARC region, Hitachi Vantara. “This report highlights that as Indian organizations operate at higher data volumes across hybrid environments, complexity and security risks increase rapidly. The organizations pulling ahead are those investing early in automation, governance, and data quality, so AI can scale predictably instead of becoming harder to control as it grows.”
Talent Gaps Drive Partner Reliance
Talent availability is emerging as one of the most significant constraints on AI growth in India. More than half (54%) cite hiring skilled workers as a top AI implementation challenge. To bridge these gaps, Indian enterprises are increasingly turning to external expertise. Seventy-six percent (76%) report working with partners or outsourcing key areas of their AI and data initiatives, higher than the global average, underscoring demand for trusted infrastructure and services partners as internal capabilities struggle to keep pace.
As Indian enterprises continue to lead in AI adoption and success, the path forward hinges on addressing infrastructure complexity, security, and talent gaps. By investing early in automation, governance, and data quality, organizations can sustain their AI momentum and unlock greater business value. With strong leadership, strategic partnerships, and a focus on modernizing data foundations, India is well-positioned to maintain its edge in the global AI race.
