Asia is leading the world in AI adoption, but a new study by Hitachi Vantara reveals that poor data quality and security risks could derail progress. The Hitachi Vantara State of Data Infrastructure Survey highlights that while 42% of Asian organizations consider AI critical—surpassing the global average of 37%—many are struggling with messy data foundations and security concerns. China and Singapore are at the forefront, with 53% and 57% of organizations, respectively, fully integrating AI into their operations. However, AI model accuracy in Asia averages just 32%, and only 30% of data is structured, pointing to significant challenges in data quality.
Data security is a top concern for 44% of Asian enterprises, higher than the global average of 38%. With data storage demands expected to rise by 123% in the next two years, the pressure to manage data effectively is mounting. Despite these hurdles, Asian companies are investing heavily in AI talent, with 71% hiring AI-skilled staff and 68% consulting external experts to bridge expertise gaps.
Adrian Johnson, Senior Vice President and General Manager at Hitachi Vantara, emphasized the need for strong data practices. “Asia’s rapid AI adoption is a reality, but without addressing data availability, security, and governance, AI’s potential will remain under-realized,” he said. The study also found that successful AI adopters in Asia credit high-quality data, strategic vendor partnerships, and robust governance frameworks as key drivers of success.
As Asia continues to push AI innovation, the focus must shift to refining data practices and building secure, scalable infrastructure. Without these foundational elements, the region’s AI momentum could stall. What steps should Asian enterprises take to overcome these challenges? Share your thoughts below.
