In the digital age, organisations are generating and storing more data than ever.
Often, this data is not well organised and exists in various forms across the organisation. It is also distributed across hybrid environments, including on-premises infrastructure, multiple cloud platforms, and edge networks. This diversity creates complexity, making it challenging for businesses to manage, secure, and extract actionable insights from their data.
Data will remain a critical asset, and organisations must navigate this complexity to maintain operational efficiency, ensure compliance, and maximise the value of their data. Those that succeed will gain a competitive advantage through lower costs and greater agility.
At the same time, AI adoption is accelerating. Organisations are implementing AI technologies to streamline operations, enhance customer experiences, and increase productivity. According to IDC’s latest Worldwide AI and Generative AI Spending Guide, AI and generative AI investments in APAC are projected to reach US$110 billion by 2028, growing at a compound annual growth rate of 24% from 2023 to 2028.
However, integrating AI into existing data systems is not easy. Businesses need to unify their data, improve accessibility, and implement security measures to make AI effective. Block storage and unified data services play a key role in enabling seamless workflows and preparing data for AI-driven insights.
Strategies for simplifying data
For APAC business and technology leaders, 2025 presents both opportunities and challenges. Scaling AI successfully will require organisations to rethink how they manage data and modernise their infrastructure.
According to the NetApp 2024 Data Complexity Report, many APAC enterprises have optimised their data for AI, with 73% of businesses reporting that their data is mostly or fully ready. Additionally, 85% of executives surveyed cite data unification as critical, leading to prioritised investments in data infrastructure.
Security and sustainability are also key considerations. Many executives are concerned about rising security risks, with 72% of APAC respondents observing an increase in challenges related to AI adoption. More than half of the region’s executives identify AI-driven security risks as their top concern, underscoring the need for strong cyber defences to mitigate vulnerabilities.
With increasing data processing and computational demands, sustainability is gaining attention. In APAC, Australia and New Zealand lead in this regard, with 84% of respondents stating that reducing their organisation’s carbon footprint is “extremely important” or “very important.” In Japan, this figure is lower, at 56%. Despite regional differences, nearly three-quarters of APAC respondents (77%) consider carbon footprint reduction important — slightly above the global average of 72%.
The rise of AI, alongside greater data and computational capabilities, has influenced corporate sustainability initiatives, with 57% of respondents reporting a “high” or “extremely high” impact. AI-driven security risks and the growing carbon footprint of data processing could prompt enterprises to adopt AI responsibly.
AI relies on unified data to deliver meaningful outcomes. A seamless data ecosystem — underpinned by block storage and unified data services — ensures that data is accessible, accurate, and scalable. By eliminating silos and enabling real-time inferencing, businesses can simplify workflows and prepare data for AI-driven innovation.
Over the next 12 to 24 months, some key priorities for APAC businesses include:
- Strengthening the AI advantage: Optimising each stage of the AI data pipeline and improving AI data governance.
- Boosting cyber resilience: Building security and rapid recovery capabilities to ensure business continuity. Strengthening cybersecurity measures also enhances protection for sensitive AI-driven data and systems.
- Undertaking cloud transformation: Migrating to the cloud while managing agility, cost, and performance.
- Modernising their data infrastructure: Transforming existing data infrastructure by integrating greater intelligence and optimising its capabilities. Investing in scalable and adaptable technologies will help meet the growing demands of AI.
- Creating common capabilities: Enabling consistent and seamless data infrastructure management across on-premises and cloud environments.
Besides increasing operational efficiency and mitigating risk, organisations that adopt this approach can also expect tangible business outcomes, including lower operational costs and improved sustainability through reduced carbon footprint and energy consumption.
Opportunities abound
For APAC organisations, 2025 will be a defining year for AI — a test of their ability to turn challenges into opportunities, such as building secure and sustainable AI frameworks and modernising data infrastructure. A unified data storage approach will help organisations streamline operations, improve efficiency, and meet the growing demands of AI-driven workloads.
By focusing on tangible strategies and investing in technologies that enable silo-free, intelligence-driven data infrastructure, businesses can seize new growth opportunities while strengthening resilience. In an AI-centric future, those with the foresight to start adapting their data infrastructure now — to make data work for their business — will be best positioned to succeed.
