Hitachi Vantara survey finds 41% of IT leaders identifying data quality as major barrier to AI success.
With the rapid adoption of AI across industries, 41% of Australian companies identify data as their top concern when implementing AI projects, but few IT leaders are taking steps to ensure proper data quality and management, jeopardising the success of AI initiatives.
That’s according to a new global survey from Hitachi Vantara, the data storage, infrastructure and hybrid cloud management subsidiary of Hitachi Ltd, which also found that 51% Australian IT leaders see AI as a must have in their organisation compared to 35% globally.
In addition, more than one-third (36) of Australian CEOs see AI as “a revolution” compared to 30% globally.
The Hitachi Vantara State of Data Infrastructure Survey reinforces the critical role that data infrastructure and data management can play in terms of overall data quality and the ability to drive positive AI outcomes.
However, just 28% of Australian companies think AI is applicable to finding new business opportunities.
“Good project management and governance” was the most common reason provided for why AI projects were successful in Australia, with 47 of Australian respondents in agreement. At the same time, 35% of respondents cite the use of high-quality data as critical for AI project success.
The survey also found that AI has led to a dramatic increase in the amount of data storage that businesses require – with the amount of data expected to increase 137% by 2026.
As a result, storing, managing and tagging data to ensure quality for use in AI models is getting harder.
The company commissioned the global survey of 1,200 C-level executives and IT decision-makers across 15 countries, including 75 from Australia. The survey found that most Australian businesses were focused on data security risks at the expense of data quality, sustainability and infrastructure management.
Key Australia findings include:
- Highlighting the disconnect with proper data management, only 44% of respondents say that data is available when they need it the majority of the time.
- Around four in ten (41%) are not taking steps to improve their data quality by tagging data for visualization, only 36% are enhancing training data quality to explain AI outputs and just under a quarter (23%) don’t review datasets for quality.
- Return on investment (45%) is top-of-mind with AI deployments followed by speed to deploy (44%) and cost and security (42%) as the highest areas of concern with their infrastructure. Additionally, 76% acknowledge that a significant data loss could be catastrophic to their operations, while 76% of respondents are also concerned that AI will provide hackers with enhanced tools.
- 25% of Australian IT leaders are addressing the inability of AI to explain module outputs through establishing AI governance frameworks compared to 36 globally while 33% of Australians are enhancing data for accurate model training compared to 38% globally.
- AI strategy is lacking sustainability considerations, as only 28% ranked sustainability as a priority in AI implementation. At the same time, 45% said they were prioritising ROI for their AI strategy.
George Dragatsis, ANZ Chief Technology Officer, Hitachi Vantara, said: “The survey makes it clear that during 2025, AI will stand out as both an opportunity and a challenge for Australian businesses. On one hand, it offers unprecedented possibilities for innovation and efficiency. AI-powered tools are enabling organisations to automate network design, optimise operations and even generate software code. These advancements promise significant productivity gains and cost savings, particularly in areas such as predictive maintenance, customer support automation, and network optimisation.
“However, the rapid adoption of AI also introduces new vulnerabilities. Automated processes could inadvertently create flawed code, leaving networks exposed to exploitation. Consequently, businesses should be focusing on handling massive data sets in a way that prioritise data resiliency, business continuity and energy efficiency and balance the benefits of AI with rigorous oversight to ensure secure and reliable implementation. This includes deploying secure development practices, conducting extensive testing of AI-generated systems, and creating transparent accountability structures for AI-driven decisions.”
Additionally, the survey reveals that as organisations advance AI initiatives, most IT leaders recognise the need for third-party support in critical areas, including:
- Hardware – To be effective, hardware needs to be secure, available 24/7 and efficient to meet sustainability goals. In the survey, 28% of IT leaders report needing assistance to create scalable, future-proof hardware solutions.
- Data Storage and Processing Solutions – Effective data solutions bring data closer to users while emphasising security and sustainability. The survey found that 22% of leaders need help with ROT data storage and data preparation, while 23% seek assistance with data processing.
- Software – Secure, resilient software is vital for protecting against cyber risks and ensuring data accessibility. 34% of IT leaders require third-party expertise for developing effective AI models.
- Skilled Staff – The skills gap remains a hurdle, with 54% of leaders building AI skills through experimentation and 27% relying on self-teaching.
Overall, 68% of Australian respondents cite using consulting external experts to successfully complete AI projects.
Nathan Knight, ANZ Managing Director, Hitachi Vantara, said: “Tapping into the experience of a strong partner can help Australian enterprises to make the right, and rightsized, investment decisions when it comes to setting up AI and data infrastructure. An experienced partner also knows its way around data preparation for AI use cases – including how to standardize formatting, how to cleanse the data, how to properly utilize it and how to ensure that data that is fed into AI models remains protected and secured.”
