Intelligent and centralised data management can boost accessibility, strengthen security: Hitachi Vantara CTO

Businesses that are investing in areas like Artificial Intelligence (AI), hybrid cloud infrastructure, and process automation are finding themselves under greater pressure to demonstrate returns on their investments. In an interview with TechCircle, Sanjay Agrawal, Chief Technology Officer and Head of Presales, India and SAARC, Hitachi Vantara, the data storage, infrastructure, and hybrid cloud management subsidiary of Hitachi, Ltd., and Chair of SNIA, (Storage Networking Industry Association), explains how intelligent automation and centralised data management can drive innovation, optimise customer experiences, and create new revenue opportunities for businesses in the data-driven world, and more. Edited excerpts:

What emerging technologies are you currently enthusiastic about and why?

We’re seeing hybrid cloud and automation revolutionising businesses, driving efficiency, intelligence, and scalability at an unprecedented pace. As we help enterprises turn data into strategic assets, ensuring they have the right foundation to accelerate innovation and growth, we see generative AI (GenAI) and intelligent automation are central to this transformation. For example, our portfolio of infrastructure and solutions to address the AI market — Hitachi iQ — developed in collaboration with Nvidia, streamlines model training, simplifies inferencing, and facilitates enterprise-wide AI adoption. Hybrid cloud provides the backbone for modern IT, preventing vendor lock-in, optimising workloads, and bolstering security across diverse environments. Our Virtual Storage Platform One (VSP One) enables seamless data mobility across on-premises, edge, and multi-cloud environments, offering a unified data fabric. In India, we are actively modernising IT infrastructure across sectors. For example, Malayala Manorama, one of the country’s leading media houses, leveraged our data infrastructure solutions to reduce their storage footprint by 66% and cut power and cooling costs by 70%, ensuring uninterrupted 24/7 operations for their print and broadcast services. With India’s rapid AI and cloud adoption, businesses have a tremendous opportunity to innovate. Our focus is to provide secure, scalable, and high-performance solutions that drive long-term growth and transformation.

How do you perceive the latest developments in the data centre industry? In what ways are you leveraging these developments to drive growth?

Data centres are evolving into AI-driven, energy-efficient, and security-first digital ecosystems. As AI workloads reshape infrastructure, businesses require high-performance computing, scalable storage, and resilient architectures to meet growing data demands. Hitachi iQ provides an AI-native environment for training and deploying models at scale while maintaining security and efficiency. With projected data storage needs exceeding 300 petabytes by 2026, scalable, secure, and efficient infrastructure is crucial. At the same time, sustainability is a growing priority. Our sustainable data solutions reduce power and cooling costs by up to 30%, enabling enterprises to meet ESG commitments without sacrificing performance. Given that 54% of IT leaders in India cite AI security risks as a major challenge, we prioritise resilient, AI-ready infrastructure to safeguard data and operations, helping customers build secure, scalable environments for long-term success.

In what ways are you utilising technology as a catalyst for innovation? Could you provide specific examples of how technology has contributed to increased business revenues or improved customer experiences?

At Hitachi Vantara, we leverage AI-driven automation, data intelligence, and sustainable infrastructure to boost profitability, enhance customer experiences, and fuel long-term growth. For regulated industries like BFSI (banking, financial services and insurance) and healthcare, technology is vital for secure, scalable, and compliant operations. AI-powered automation and data intelligence improve operational efficiency, reduce costs, and enhance customer experiences.

A strong example of tech driving business success again is Malayala Manorama, which ensured 100% data availability and 24/7 operations across its media businesses by leveraging Hitachi Vantara’s virtual storage platform and advanced servers. This resulted in faster content delivery, improved audience engagement, and uninterrupted digital experiences, directly enhancing customer satisfaction. The organisation also significantly lowered operational costs, enabling reinvestment in digital transformation. Through AI, automation, and intelligent infrastructure, we’re helping businesses to drive innovation, optimise customer experiences, and create new revenue opportunities in the data-driven world.

With the company's significant investment in data storage solutions, what technological infrastructure and policies are essential for achieving success?

Success in data storage solutions depends on a combination of robust technological infrastructure and well-defined policies that ensure efficiency, security, and long-term scalability. As data volumes grow, businesses require intelligent, AI-driven storage architectures that integrate seamlessly across on-premises, hybrid, and multi-cloud environments. These architectures must be scalable and resilient, allowing organisations to process and analyse data efficiently while maintaining uninterrupted operations.

Automation is another key factor in optimising storage performance. AI and machine learning-powered systems can help businesses streamline storage provisioning, predict capacity needs, and optimise workloads — reducing operational complexity and improving efficiency. Additionally, hybrid cloud flexibility is becoming essential, enabling organisations to scale storage resources as needed while optimising costs.

Security and compliance are also critical in today’s evolving threat landscape. Zero-trust security models, built-in encryption, and governance policies help safeguard sensitive data while ensuring compliance with global regulations such as GDPR and CCPA. As cyber-threats grow, immutability and policy-driven automation are also crucial in preventing data loss and ensuring business continuity.

Furthermore, sustainability is now a core consideration in data infrastructure decisions. Energy-efficient architectures can help organisations reduce power and cooling costs while supporting broader ESG commitments. As enterprises continue to expand their digital footprint, balancing performance, security, and sustainability will be key to building resilient, future-ready storage environments that support long-term business success.

GenAI has generated considerable excitement in the corporate world. Do you believe that businesses are adequately prepared for the potential success of GenAI?

GenAI presents significant opportunities for business transformation, but success depends on more than just adoption — it requires a strong data foundation, scalable infrastructure, and responsible governance. While many organisations are eager to embrace GenAI, challenges such as data quality, AI scalability, and regulatory compliance will ultimately determine its impact.

One of the biggest barriers to effective GenAI implementation is data readiness. AI models are only as good as the data they are trained on, yet many enterprises struggle with fragmented, biased, or poor-quality data. Without a structured approach to data governance, organisations risk unreliable outputs and compliance issues.

Scalability is another critical factor. Businesses must ensure they have flexible infrastructure that can support AI workloads across hybrid and multi-cloud environments while optimising performance and cost. Security also remains a key concern, as AI adoption introduces new risks, requiring robust governance frameworks and real-time monitoring to prevent bias, misinformation, and security threats.

Rather than viewing GenAI as a quick-fix innovation, organisations should prioritise long-term AI strategies, focusing on trusted data ecosystems, scalable architectures, and responsible deployment models. By doing so, they can move beyond experimentation and unlock sustainable business value from AI-driven insights.

When conducting competitor benchmarking, which specific areas of technology do you believe require improvement?

In the current technology landscape, several key areas present opportunities for improvement across the industry. One significant challenge is data fragmentation, which often leads to disconnected data silos and hinders effective AI adoption. Moving towards centralised, intelligent data architectures is crucial for ensuring data accessibility, security, and scalability.

Additionally, cybersecurity remains a critical concern, especially with the rise of AI-powered threats. Implementing zero-trust security models, AI-driven threat detection, and automated security frameworks is essential for building resilience against evolving risks.

Organisations also face challenges with cloud cost management. As hybrid and multi-cloud strategies become more prevalent, optimising costs while ensuring effective workload placement and governance is increasingly important. Smarter automation and resource allocation practices will be vital for maximising the value derived from cloud investments. Overall, the focus should be on redefining industry standards to support businesses in remaining secure, scalable, and innovation-driven.

What specific areas within the realm of technology will be the primary focus for your organisation in the next one year?

Hitachi Vantara is prioritising robust data platforms to help customers harness their data while modernising legacy systems. As data volumes grow, intelligent, scalable, and AI-ready infrastructure is needed for high-quality insights and informed decision-making. We are also concentrating on AI-driven insights across industries. Given that many IT leaders identify data quality as a major challenge, we aim to help organisations establish AI-ready data ecosystems with governed, bias-free data for more accurate decision-making. Sustainability is a top priority. We are developing energy-efficient data centres, implementing AI-driven resource optimisation, and promoting circular economy models to reduce environmental impact while maintaining performance.