New research reveals a region outpacing global AI adoption yet hindered by messy data foundations and security concerns
Asian enterprises are ahead of the curve when it comes to embedding AI into core operations. This is according to new research from Hitachi Vantara, the data storage, infrastructure, and hybrid cloud management subsidiary of Hitachi, Ltd. (TSE: 6501). While 37% of organisations worldwide now consider AI critical to their function, the figure is 42% in Asia. Certain markets stand out even more, with China and Singapore topping the list globally with 53% and 57% respectively indicating that AI is now critical to their organisation’s operations, underscoring the region’s decisive shift from experimentation to full-scale AI adoption.
The Hitachi Vantara State of Data Infrastructure Survey, which included 1,200 global respondents—including 325 in India, China, Singapore, Indonesia, and Malaysia—shows that while Asia is moving beyond initial AI pilots, organisations in the region are still struggling with fundamental data challenges.
Struggling With Basic Data Foundations
Despite ambitions to integrate AI more deeply, critical metrics remain underwhelming: on average, Asian enterprises estimate that their AI models produce accurate outputs just 32% of the time, and data is available where and when it’s needed only 34% of the time. Even more concerning is the quality of data itself, with a mere 30% deemed structured, indicating that most information feeding into AI systems is messy and unrefined.
These figures suggest that instead of reaping the rewards of mature AI ecosystems, many Asian businesses are still grappling with basic implementation hurdles. Limited data quality and availability likely inhibit AI initiatives from achieving the breakthroughs leaders envision. While the region boasts many organisations declaring AI as critical, these lofty aspirations risk being undermined by the poor state of underlying data conditions.
Skyrocketing Data Volumes Compound Complexity
Compounding the issue is the looming explosion of data volumes. With respondents in Asia expecting data storage demands to rise 123% in the next two years, enterprises will find it even harder to ensure that AI models receive clean, timely inputs. Data security concerns add another layer of complexity; 44% of Asian respondents cite it as a top worry, surpassing the global average of 38%. This pressure resonates strongly in India and Indonesia, where 54% and 50% highlight data security among their main concerns when implementing AI, further complicating the pursuit of trustworthy AI outcomes.
In this environment, without decisive action to improve data structuring, availability, and quality, Asian firms may find their AI initiatives stall, delivering inconsistent and unreliable results rather than the promised transformative value.
Investing in Skills and External Expertise
Meanwhile, companies in Asia are shoring up their capabilities: 71% of Asian enterprises are hiring staff with AI-relevant skills (vs. 64% globally) and 68% are consulting external experts (vs. 61% globally), indicating a concerted effort to close expertise gaps and implement AI responsibly. Notably, respondents from Singapore, Indonesia, India and China were all engaging experts or hiring AI experts at rates higher than the global average. However, this was not the case for Malaysian respondents who relied far more on being self-taught (50%) than their counterparts, suggesting a different approach to capability building in the market.
Data Quality, Vendor Partnerships, and Project Management Drive Success
Achieving sustained AI advantage in Asia is not just about scaling up; it requires laying the right groundwork for AI to thrive. Among the region’s most successful AI adopters, 40% credit the use of high-quality data for their achievements, above the 38% global average.
Equally important are strategic collaborations with experts outside the organisation: 39% of Asia’s AI frontrunners cite partnerships with AI vendors and specialists as the key to success, outpacing the 37% global norm. Rounding out the trio of critical factors is strong project management and governance. In Asia, 45% of top performers credit robust governance frameworks, well above the 37% global figure, underscoring the value of clear processes and accountability structures. These figures underscore that reliable data, knowledgeable partners and disciplined project management form a powerful foundation for navigating AI’s complexities.
“Asia’s rapid AI adoption is not a promise; it’s a reality,” said Adrian Johnson, Senior Vice President and General Manager, The Americas and Asia Pacific at Hitachi Vantara. “The region’s markets show that when organisations pair advanced adoption with data best practices, AI can transcend pilot projects to become truly transformative. However, leaders must recognise that data availability, security, quality, and governance are not optional. Without them, AI’s potential will remain under-realised.”
Turning Data Strengths into Long-Term Advantages
As Asia matures in AI application, refining underlying data practices will ensure its momentum endures. Converting unstructured data into refined, AI-ready information can support more accurate models, while robust security measures and governance frameworks help meet regulatory demands and align with global best practices.
Having a Trusted Partner Can Help
Additionally, the survey reveals that as organizations advance AI initiatives, most IT leaders in Asia recognize 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, 36% of IT leaders report needing assistance to build AI models/LLMs.
Data Storage and Processing Solutions – Effective data solutions bring data closer to users while emphasizing security and sustainability. The survey found that 30% of leaders need help with reducing redundant, obsolete, or trivial (ROT) data storage, 29% need help with data preparation, and 34% seek assistance with data processing.
Software – Secure, resilient software is vital for protecting against cyber risks and ensuring data accessibility. 39% of IT leaders require third-party expertise for developing effective AI models.
Skilled Staff – The skills gap remains a hurdle, with 42% of leaders building AI skills through experimentation and 30% relying on self-teaching.
“By aligning AI expansion with data integrity and strategic resource investments, Asia’s enterprises can fully capitalise on their early lead,” added Johnson. “This focus on foundational data elements, along with strategic partnerships and effective governance, can ensure AI initiatives deliver truly transformative and enduring value.”
