CIO Influence Interview with Jason Hardy, CTO at Hitachi Vantara

How can IT leaders tap into the GenAI solutions market more effectively? Jason Hardy, CTO at Hitachi Vantara weighs in with some pointers:

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Hi Jason, take us through your biggest IT leadership takeaways and moments, tell us more about your role at Hitachi Vantara.

I’m Jason Hardy, as Chief Technology Officer for Artificial Intelligence at Hitachi Vantara, I’m responsible for the creation and curation of Hitachi Vantara’s AI strategy and portfolio.

Can you share some top highlights from Hitachi Vantara’s recent 2024 AI Infrastructure study? What should IT teams and leaders pay more attention to in 2024 based on this research?

This research identifies various ways IT leaders can tap into the expanding market for generative AI (GenAI) solutions in the United States and Europe.

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Here are key takeaways from the research:

• Upskilling the Workforce: There’s a clear need for employee education on GenAI capabilities (61%). This presents a chance for Hitachi iQ to develop training programs that effectively empower users to leverage GenAI.
• Building Trust and Transparency: Only 44% of organizations have comprehensive GenAI policies. Hitachi iQ can help bridge this gap by providing tools and best practices for responsible AI development and deployment.
• Optimizing Infrastructure: Just 37% of respondents feel their infrastructure is ready for GenAI. Hitachi iQ’s expertise can help assess and optimize existing systems or recommend cloud-based solutions for scalability.
• Collaboration is Key: The research suggests room for improvement in collaboration across teams. Hitachi iQ can facilitate communication and break down silos to ensure successful GenAI project execution.

To ensure long-term success in GenAI projects, the broader stakeholder ecosystem must be educated. IT decision-makers must invest in employee education, ensuring that relevant stakeholders are adequately informed for successful planning and execution.

What are some of the biggest impediments to modernizing IT infrastructure in today’s business ecosystem?

The cost of infrastructure to support GenAI is notable. However, we’re now seeing an improvement in the technology, increasing ROI across the board, as GPUs become more powerful and efficient to get more meaningful results faster .

At Hitachi Vantara, we have invested in engineering a portfolio that can drive a 20x improvement in GPU performance and enable better economics for scaling and density, and modern technology that can support these workloads.

We also see this as not just a data center world. We live in a hybrid world, so we can best support our customers across a hybrid ecosystem. Having workloads supported on-prem or in the cloud, depending on the sensitivity of data, addresses another top concern about enterprise GenAI adoption.

The lack of skilled personnel is another major barrier to GenAI adoption. Businesses need professionals with expertise in machine learning, data science and deep learning to develop and manage GenAI models. Additionally, interpreting and utilizing GenAI outputs effectively,  as well as integrating them seamlessly into existing workflows, requires a strong understanding of both the technology’s strengths and limitations.

Over time, we’ll continue to see costs lowered as the technology improves, which will help lower the barrier to entry and increase the value of investments. Additionally, addressing the shortage of skilled personnel by investing in training and development will be crucial for successful GenAI adoption. By combining advancements in technology with a skilled workforce, companies can maximize ROI and create successful use cases that significantly outweigh the initial investments in AI adoption.

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For IT leaders looking to enhance their IT infrastructures with GenAI solutions, what points should be kept in mind?

The need for guidance within the IT and data infrastructure space is evident, with only 44% of organizations having well-defined and comprehensive GenAI policies, according to our recent study with ESG.

While GenAI solutions offer immense potential, their true value hinges on having an AI-ready infrastructure.  Our recent ESG research suggests that 37% of IT leaders feel their current setup is optimized for GenAI, and 44% of organizations have well-defined and comprehensive policies regarding GenAI in place.

It is clear that there is a gap between the promise of GenAI and its implementation within organizations. This highlights the need to shift from viewing AI solely as a product to focusing on the outcomes it enables. The crucial groundwork lies in creating this AI-ready foundation:  IT leaders who will champion and support the desired AI-powered solutions.

Key Considerations for IT Leaders:

• Data Quality is Paramount: GenAI solutions are data-driven. Addressing data quality issues promptly ensures the accuracy and effectiveness of your AI initiatives.
• Modernization is Essential: Legacy infrastructure can hinder GenAI implementation. Evaluate modernization needs to create a robust and efficient platform for GenAI solutions.
• Embrace Flexibility and Transparency: The complexities of GenAI data demand adaptable and transparent data management practices. Prioritize systems that can handle evolving data needs while maintaining clear audit trails.

IT leaders play a pivotal role in integrating GenAI solutions while safeguarding data integrity.  Security, data quality and infrastructure flexibility are important in building a resilient and modern IT environment capable of withstanding external threats and supporting GenAI effectively.

By prioritizing these considerations and fostering an AI-ready culture, IT leaders can unlock the transformative potential of GenAI solutions for their organizations.

Also Read: Security as a Business Enabler: How Collaboration Between IT and Business Teams Strengthens Data Protection

Can you talk about the top data security and privacy issues that affect IT teams and organizations today, and what should IT leaders keep in mind as they try to adapt to new age threats while trying to provide secure systems to distributed teams?

According to a recent report from Hitachi Vantara, 75% of IT leaders worry their data infrastructure won’t scale to meet their evolving needs. A critical component of ensuring your IT teams are equipped with the necessary tools to protect customer and internal data starts with proper data infrastructure at the point of implementation.

In fact, 37% of enterprise IT leaders surveyed in our recent study with ESG on GenAI implementation cited data security as the most important characteristic in enterprise data and storage infrastructure.

This points to an evident challenge among IT leaders related to ensuring data quality while grappling with regulatory requirements – and GenAI has only further driven this challenge.

Notably, 56% of IT leaders in our latest study listed improved accuracy as a reason for retraining GenAI models. For GenAI models to be accurate and relevant, as much data as possible must be collected in every scenario. Since organizations won’t be using a single model for everything, they’ll need to create a way to access all the necessary data with the right guardrails and security constructs wrapped around it for the individual use cases.

If you had to share five points of the current State of Organizational IT before we wrap up, what would you share?

Customers are looking to advanced analytics and artificial intelligence to optimize their growth. In the era of vast volumes of data being consumed or created, offering customers reliable, secure, sustainable and scalable data infrastructure solutions is paramount.

Providing a flexible, robust data infrastructure for unparalleled performance and capacity is a necessity. Developing and managing data platforms that scale on demand can empower customers with limited resources.

Cybersecurity is even more paramount in this era of increased data storage demands. Regardless of the data infrastructure solution being offered, it must be capable of safeguarding the integrity and availability of customer data. This is necessary for customers seeking to shield themselves from potential compromise and meet the most recent compliance regulations.

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