APAC enterprises will increase public cloud storage spend and capacity, while embracing opportunities for AI/ML adoption

Asia-Pacific organisations are increasing their investments in public cloud storage to drive infrastructure migration, cloud modernisation, and new data security and recovery requirements. According to the 2024 Wasabi Global Cloud Storage Index, 93% of APAC organisations expect to increase the amount of data they store in the public cloud in 2024, up 8% from last year. Commissioned by Wasabi Technologies, the hot cloud storage company, and conducted by Vanson Bourne, the Wasabi Global Cloud Storage Index uncovers the changing attitudes toward public cloud storage adoption, the factors that influence storage buying decisions, and the top priorities when it comes to budget, capacity, vendor selection, billing, features and satisfaction.

The 2024 Cloud Storage Index shows 47% of respondent’s cloud storage bills are allocated to various data operations and retrieval fees. APAC enterprises are no exception, with a similar proportion of billing allocated to fees. Japan and Australia indicated an even higher proportional mix of fees, at 50%. Nevertheless, countries across the APAC region continue to increase their budgets and the amount of data they store in the cloud to support new IT initiatives like cloud infrastructure migration and modernization, and to enhance backup, recovery, and other data security requirements.

“Despite many organisations struggling to control cloud costs due to complex and ubiquitous fee structures, we’re still seeing continued growth and adoption across the APAC region, particularly in Japan,” said Andrew Smith, Senior Manager of strategy and market intelligence at Wasabi Technologies, and a former IDC analyst. “44% of APAC respondents we surveyed consider their organisation’s IT services adoption strategy to be ‘cloud-first,’ indicating they will continue to prioritize cloud services adoption over any alternative requiring owned or on-premises infrastructure.”

AUSTRALIA

100% of Australia respondents say their organisation will adopt, or will plan to adopt AI/ML applications or services within the next 12 months

• 89% of Australia respondents say they expect to increase the amount of data their organisation stores in the public cloud in 2024. This is slightly below the APAC average of 93%, but still an impressively high result
• 83% of Australian respondents say they expect their organisation’s public cloud storage budget to increase in 2024
• Similar to Japan, Australia also has a slightly higher proportional mix of spending on fees, with respondents saying 50% of their cloud storage budget is allocated to fees. This unfavorable mix is likely part of the reason why 50% of Australian respondents say their organisation exceeded budgeted spend on cloud storage last year
• All of our Australia respondents (100%) say their organization is adopting or planning to adopt some form of AI/ML application or service within the next 12 months. Certainly, this indicates an eager willingness to expand AI/ML solutions and strategies in Australia, but this endeavor won’t come without infrastructure-related challenges. Specifically, Australia respondents indicated a high rate of concern with addressing new data backup, protection and recovery requirements associated with AI/ML adoption

JAPAN

Japan is planning for continued investments in cloud storage, despite an unfavorable mix of spending on storage-related data fees

• 94% of Japan respondents say they will increase the amount of data they store in the public cloud in 2024, a slightly higher rate than the global average of 93%
• However, a large proportion of storage spending in Japan goes to storage fees, not storage capacity. Japan organisations say half their cloud storage bill (50%) is consumed by storage fees like data operations, retrieval, transfer, and egress
• These fees are part of the reason why 55% of Japan organisations say they exceeded their budgeted spend on cloud storage
• Whan asked about AI/ML initiatives, generative AI ranked #1 among Japan as the leading workload planned for deployment, or currently deployed
• When asked about the top priorities driving AI/ML adoption in 2024, Japan respondents ranked accelerating innovation and development cycles for existing products/services and improving customer facing product/services as their top drivers
• Thinking specifically about storage-related AI/ML challenges, Japan ranked unpredictable storage cost patterns (e.g., egress fees, data access fees), as a leading concern

SINGAPORE

Singapore prioritises IT cloud services sustainability, and looks to drive operational improvements through AI/ML solution adoption

• For the second year in a row, Singapore ranked sustainability (in terms of infrastructure architecture, service provider initiatives/commitments, or built-in tools for things like carbon footprint calculation) as the #1 most important consideration when it comes to choosing a cloud storage provider/service
• Singapore indicates a lower proportional mix of cloud storage fees (with only 44% of billing allocated to fees, on average). However, counterintuitively, Singapore indicated the highest rate of budget excess among all countries surveyed; with 66% of Singapore respondents saying their organization exceeded budgeted spend on cloud storage in 2023
• Singapore ranked operational improvements as the #1 driver for AI/ML implementation, and chose AI/ML solutions for security and compliance (e.g., advanced anomaly detection) as the top workload their organization has implemented or is planning to implement solutions for

“It comes as no surprise that APAC followed suit with the global trend that ranked AI/ML incorporation as a top priority,” said Michael King, VP & GM, Asia Pacific and Japan, Wasabi Technologies. “Enterprises are realising that to maintain a competitive edge, they must find new and innovative ways to deploy AI capabilities, both for internal processes and as offerings to customers. That is why many are looking to increase their storage amount to host the mountain of data that is necessary to run AI/ML applications that have become so critical.”