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Asian enterprises lead global AI adoption but face data and security challenges

Asian enterprises lead global AI adoption, but poor data quality, availability, and security risks could hinder growth, Hitachi Vantara warns.

New research highlights the rapid pace of AI integration across Asia, with firms in China and Singapore taking the lead, yet facing key obstacles like poor data quality and security concerns.

Asian firms ahead in AI integration

Asian enterprises are leading the world in adopting AI as a core business strategy, according to the latest research by Hitachi Vantara, the data management subsidiary of Hitachi, Ltd. Globally, 37% of organisations view AI as critical to their operations. In Asia, this figure rises to 42%, demonstrating the regionโ€™s early embrace of the technology. Notably, 53% of companies in China and 57% in Singapore place AI at the core of their business strategies, the highest globally.

The survey, which included 1,200 global respondentsโ€”325 of whom were from countries like India, China, Singapore, Indonesia, and Malaysiaโ€”shows that many organisations in Asia have moved beyond experimental AI pilots. However, fundamental issues related to data quality and availability threaten to limit their progress.

Poor data foundations hinder AI success

Despite the high adoption rate, Asian enterprises face significant challenges with data reliability. On average, their AI models produce accurate outcomes only 32% of the time. Furthermore, data is readily available for use in just 34% of cases. Adding to this, only 30% of the data used is structured, which highlights the extent of unrefined and unorganised information feeding into AI systems.

This lack of structured data and availability suggests that many businesses are unable to maximise the benefits of AI due to these foundational problems. The report warns that without addressing these issues, AI programmes will yield inconsistent and unreliable results, preventing the desired breakthroughs.

Data volumes and security risks escalate

The problem is expected to worsen as data volumes grow. Respondents in Asia anticipate a 123% rise in data storage needs over the next two years. With this surge, ensuring clean and timely inputs for AI models will become increasingly difficult.

Additionally, data security remains a major concern, with 44% of Asian respondents highlighting it as a key issueโ€”higher than the 38% global average. Security concerns are particularly pressing in India (54%) and Indonesia (50%). Without sufficient measures, businesses risk setbacks in their AI strategies.

Boosting skills and partnerships

In response, many companies in Asia are focusing on addressing their internal expertise gaps. About 71% of enterprises in the region are hiring AI-skilled staff, compared to 64% globally. Meanwhile, 68% are seeking external experts, showing a commitment to gaining specialised knowledge and ensuring responsible AI implementation.

However, the approach varies across countries. While firms in Singapore, Indonesia, India, and China are actively seeking expert guidance, companies in Malaysia are more self-reliant. Half of the Malaysian respondents reported learning through self-teaching rather than relying on external support.

Laying the foundation for long-term AI success

The study underscores that scaling AI effectively requires more than rapid adoptionโ€”it demands robust foundations. Among the top AI performers in Asia, 40% attribute their success to using high-quality data, surpassing the 38% global average. Strategic partnerships also play a role, with 39% of leading Asian firms citing collaborations with AI vendors as key to their progress.

Strong project management and governance frameworks have also proven critical. In Asia, 45% of successful companies credit effective governance with helping them manage AI projects, well above the 37% global figure. Clear structures and accountability ensure smoother implementation and better outcomes.

โ€œAsiaโ€™s rapid AI adoption is not a promise; itโ€™s a reality,โ€ said Adrian Johnson, Senior Vice President and General Manager, The Americas and Asia Pacific at Hitachi Vantara. โ€œThe regionโ€™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, AIโ€™s potential will remain under-realised.โ€

Partnering with experts for sustainable AI

As organisations across Asia expand their AI efforts, many are turning to trusted third-party partners to help with critical aspects, including hardware, data storage, and software.

  • Hardware: Efficient and secure hardware is crucial. The survey shows that 36% of IT leaders seek external support in building AI models.
  • Data storage and processing: Data management is another priority, with 30% of leaders seeking help in reducing redundant or obsolete data and 34% requiring assistance with data processing.
  • Software: Reliable software is essential to safeguarding data. Around 39% of leaders need expert support to develop robust AI models.
  • Skilled staff: The skills gap remains a major hurdle, with 42% of IT leaders relying on experimentation and 30% using self-teaching to build AI capabilities.

โ€œBy aligning AI expansion with data integrity and strategic resource investments, Asiaโ€™s enterprises can fully capitalise on their early lead,โ€ added Johnson. โ€œThis focus on foundational data elements, along with strategic partnerships and effective governance, can ensure AI initiatives deliver truly transformative and enduring value.โ€

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