As the adoption of
artificial intelligence (AI) accelerates across India, 54% of Indian IT leaders identify security gaps as significant barriers to AI success, according to the
Hitachi Vantara State of Data Infrastructure Survey. 45% of respondents are concerned about a data breach from an AI-enabled attack and 35% are concerned about the inability to recover data after a ransomware or kill-ware attack
.
The survey reveals that, despite the rise in AI-driven innovations, Indian enterprises are struggling to align data quality, sustainability, and resilient practices with AI’s growing demands, putting long-term success at risk. The findings highlight the urgent need for data governance practices that include robust ransomware protection services and infrastructure to ensure Indian businesses can effectively secure and recover their data in an increasingly complex data landscape.
Click here to download the Hitachi Vantara State of Data Infrastructure Report
The survey, conducted among 1,200 IT decision-makers across 15 countries—including 100 from India—reveals the transformative potential of AI and the pressing need for robust data infrastructure. Key India-specific findings include:
● 58% report AI initiatives' success relies on high quality data
● 43% are concerned about having sufficient data quality to train AI, compared to 37% globally.
● 37% expressed concern about ethical and legal issues related to AI, notably higher than the global average of 28%.
● 36% are concerned about hiring skilled workers for AI initiatives, compared to the global figure of 31%.
● 43% are concerned about AI’s impact on our sustainability, exceeding the global concern of 31%.
● 54% of Indian enterprises cite cybersecurity as their top priority in AI implementation, overshadowing high implementation costs at 43%
Recognizing the importance of data quality, 58% of Indian IT leaders agree that “using high-quality data” is the most common reason AI projects succeed. However, AI has led to a dramatic increase in the amount of data storage that Indian businesses require, with the amount of data expected to increase 129% by 2026. This growth is exacerbating the challenge of integrating new AI systems with existing legacy infrastructure.
“India's journey toward AI-driven innovation is accelerating at a remarkable pace, but the path is not without its challenges,” said
Hemant Tiwari, Managing Director and Vice President of India and SAARC Region, Hitachi Vantara. “With more organizations expecting their data storage demands to grow exponentially in the coming years, the need for robust data infrastructure has never been more critical. Our survey shows that while Indian enterprises embrace AI, data security and governance, gaps persist in cyber security and sustainability, potentially impeding long-term success. Bridging these gaps requires a strategic focus on modern infrastructure solutions that prioritize data quality, energy efficiency, performance, resiliency and risk mitigation— critical enablers for sustainable growth in the AI era.”
The Disconnect Between AI Potential and Data Quality
A surprising takeaway from the research was the gap between how many IT leaders say data quality is essential for implementing new technologies like GenAI and how few actually prioritize it in practice. While 58% of Indian IT leaders identify data quality as essential for implementing technologies like GenAI, only 43% express concerns about the availability of high-quality training data. This disconnect suggests that, despite acknowledging its importance, many IT leaders are not adequately prioritizing the foundational role of data quality in AI deployment, potentially limiting AI’s effectiveness.
AI Growth Outpaces Infrastructure Readiness
As Indian organizations harness AI for competitive advantage, unstructured data—comprising nearly 70% of data in India—presents challenges in quality and accessibility. Businesses are also facing barriers due to the limited adoption of foundational practices:
● 8% of Indian respondents experiment with AI across all projects, while 5% use small sandboxes to test AI models before full implementation.
● 21% of Indian respondents cite the lack of proper data infrastructure as a barrier to ensuring AI is sustainable and responsible.
“AI adoption thrives on trust in data and outcomes. Without a solid foundation in data quality and governance, AI’s potential remains unfulfilled,” said
Sanjay Agrawal, CTO and Head of Presales, India and SAARC, Hitachi Vantara. “Our survey shows that Indian organizations are embracing AI but must address gaps in infrastructure and sustainability to drive long-term value.”
The Role of Infrastructure in Bridging the Gap
Modern data infrastructure is critical to overcoming these challenges. Hitachi Vantara’s sustainable solutions empower organizations to enhance data quality, reduce energy consumption, and mitigate risks.
Key survey insights from Indian respondents include:
● 37% seek ROT (redundant, obsolete, trivial) data storage solutions to improve accessibility and cost efficiency.
● 36% identify a skills gap in AI implementation, with many relying on third-party expertise for AI model development and data processing.
● 39% need help with sustainable AI implementation, as opposed to 27% globally, highlighting a demand for infrastructure solutions that support long-term AI viability.
● 32% require assistance with strategic AI deployment and integration, which emphasizes the need for robust, scalable infrastructure to support AI at scale.
