Breaking Down Data Silos in the Age of AI: How Hitachi Vantara Sees The A/NZ Opportunity Evolving

Data volumes are exploding and while this provides an unprecedented opportunity for organisations to leverage and benefit from AI, it’s also a challenge of an almost unheard-of scale to overcome.  

According to new research into the Australia market by Hitachi Vantara, 43% of IT leaders view AI as essential to their operations. This in itself is interesting as it is significantly higher than the 34% global average.  

While this enthusiasm presents an opportunity for local organisations to take a leading position on innovation, AI ambitions face a critical challenge: as data volumes are set to explode by 137% by 2026, many organisations find themselves hamstrung by fragmented infrastructure and siloed data management systems. 

Only 44% of Australian companies can reliably access their data when needed, while 41% identify poor data quality as their top barrier to AI success. For A/NZ enterprises navigating the complexities of modernising legacy infrastructure while balancing cloud adoption, cost pressures, and compliance requirements, the path forward requires a fundamental shift in how data is stored, managed, and accessed. 

The Hidden Cost of Data Fragmentation 

Nathan Knight, A/NZ Managing Director at Hitachi Vantara, said that the foundation of successful AI implementation lies in addressing long-standing data challenges. "When you look at the dark data that exists in organisations, it accounts for somewhere between 60 to 80% of all data," Knight said.

"This is, by definition, data that hasn't had any ability to be able to bubble up and deliver value into the organisation." 

According to the Hitachi Vantara research, the consequences of poor data management are far-reaching. Organisations struggle with data classification, understanding the complexities of different data sources, and the inability to leverage historical datasets for AI training. 

Knight pointed to a practical example from their customer base: "One of the organisations that we've been working with for the last 15 years really had a lens on that legacy of data,” he said. “They had seven different generations of data that were delivering different services to their organisations." A project to consolidate and de-silo that data allowed the client to reduce their data management workforce by 35%, freeing up those skills to redeploy into innovation and product development roles. 

"You need to drive simplification in terms of the way that you manage and augment some of that legacy," Knight said. "Some of the great things that Hitachi has with some of its new platforms allows you to be able to sit a technology stack on top of legacy data and be able to pull that and feed that into a new platform." 

Achieving a Renewed Focus on Governance 

Another benefit of this approach is that it allows Hitachi Vantara and its customers to address one of the survey's most concerning findings: only 25% of Australian IT leaders have established AI governance frameworks, compared to 36% globally. This is a part of the organisation’s risk profile that is increasingly high priority to boards.  

Knight identified four key areas for building proper governance: explainability, auditability, ethical standards and regulations, and organisational governance that flows through multiple stakeholders. 

"We need structure around the way that we operate," Knight said. "It really does start with explainability and your ability to be able to understand why we are making AI decisions and what we believe the AI outcomes are going to be. The critical piece in that is your ability to be able to audit that pathway." 

Another key area that has become a governance priority is sustainability. As power-hungry AI workloads increase, sustainability becomes a renewed talking point, and the survey reveals that already 28% of Australian organisations prioritise sustainability in AI implementation. Knight argues that sustainability and performance don’t need to be mutually exclusive: "For us, in terms of cycle to cycle platform, we're seeing a 40% reduction in terms of CO2 that is going from one platform to another, and that starts to have downstream benefits in terms of data centre footprint," he said. 

Future-Proofing Through Partnership 

The other big question hanging over organisations is how they will get going with their AI ambitions. Building the skills to deliver AI capabilities internally is beyond many organisations. Consequently, 68% of Australian respondents rely on external experts to successfully complete AI projects.  

Knight sees this as a positive trend, particularly if the partnership is strategic in nature. "The overall understanding in Australia is that we need to find the right organisations to partner with us," he said. "AI is strongest as an ecosystem play – we’ll go and understand who's working with who and the depth of the relationships, and through that we’re able to de-risk that journey to AI and particularly how the organisation understands, optimises and uses data." 

Like with digital transformation projects before it, success with AI relies on more than new technology. It demands a fundamental rethinking of data architecture, governance frameworks, and partnership strategies. As Australian enterprises continue to lead global AI adoption rates, those that successfully break down their data silos today will be best positioned to capitalise on tomorrow's AI innovations. 

Read the full Hitachi Vantara research report here.