AI adoption in Asia is surging ahead of the global curve. Still, fundamental challenges in data quality, security, and availability threaten to stall progress, according to a new study by Hitachi Vantara.
Asia Leads in AI Adoption, But Challenges Remain
The Hitachi Vantara State of Data Infrastructure Survey reveals that 42% of Asian enterprises now consider AI critical to their operations, surpassing the 37% global average. AI has transitioned from experimental phases to full-scale implementation in markets like China (53%) and Singapore (57%).
However, despite this rapid expansion, data challenges remain a major roadblock. AI models in the region produce accurate results only 32% of the time, and data is available when needed just 34% of the time. Even more concerning, only 30% of data is structured, meaning most AI systems are working with unrefined and inconsistent inputs.
Skyrocketing Data Volumes Add to Complexity
The issue is further compounded by the exponential growth in data. Asian enterprises expect data storage demands to increase by 123% within two years, making it even more difficult to manage and clean incoming information.
At the same time, data security concerns are mounting, with 44% of Asian organisations citing it as a top challenge, compared to the 38% global average. In countries like India (54%) and Indonesia (50%), security is a primary barrier to AI adoption, highlighting the urgent need for robust cybersecurity measures.
Investing in Skills and Expertise to Bridge the Gap
Despite these hurdles, Asian enterprises are proactively investing in AI talent and expertise.
- 71% of companies in Asia are hiring AI-skilled employees (vs. 64% globally).
- 68% are bringing in external AI experts to guide their initiatives (vs. 61% globally).
- Markets like Singapore, India, Indonesia, and China lead in AI skill acquisition, while Malaysia takes a more self-taught approach, with 50% of enterprises relying on internal learning rather than external expertise.
What Drives AI Success? Data, Partners, and Governance
The study identifies three key factors that distinguish AI frontrunners in Asia:
- High-Quality Data – 40% of leading AI adopters credit well-structured, clean data as a critical success factor.
- Strategic Partnerships – 39% rely on AI vendors and consultants, exceeding the 37% global average.
- Strong Governance – 45% of AI leaders emphasise disciplined project management and clear accountability structures (vs. 37% globally).
According to Adrian Johnson, Senior Vice President and General Manager at Hitachi Vantara, “Asia’s rapid AI adoption is not a promise; it’s a reality. But without strong data availability, security, and governance, AI’s transformative potential will remain under-realized.”
Strengthening AI Foundations for Long-Term Success
To maintain its AI leadership, Asia must focus on improving data practices, security measures, and governance frameworks. The report also highlights the critical role of third-party support in addressing AI infrastructure challenges:
- Hardware – 36% of IT leaders need assistance in building AI models and large language models (LLMs).
- Data Storage & Processing – 34% seek help in managing, securing, and optimising data processing.
- Software – 39% require third-party expertise to develop secure and resilient AI models.
- Skilled Staff – 42% of leaders rely on hands-on experimentation to build AI skills, while 30% rely on self-teaching.
“By aligning AI expansion with data integrity and strategic investments, Asia’s enterprises can fully capitalise on their early lead,” Johnson added. “Strong data foundations and expert partnerships will ensure AI initiatives deliver truly transformative and lasting value.”
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