Nutanix, a leader in hybrid multicloud computing, has released the “Nutanix State of Enterprise AI Report for Asia-Pacific and Japan (APJ). The report highlights enterprise artificial intelligence (AI) deployment and trends. It also delves into how planned implementations will affect staffing, IT, and cloud investments in the year ahead. Additionally, it indicates that AI could be a priority for 90% of APJ organisations and that most are planning investments to support it—whether to modernise their IT infrastructure (84%) or to advance their edge strategy (81%).
The report is based on a global research study conducted by Vanson Bourne, on behalf of Nutanix. It surveyed 200 IT, DevOps, and Platform Engineering decision-makers between July and September 2023. The respondent base spanned multiple industries and business sizes in the APJ region
Key Findings of the Study
- APJ organizations plan to embrace AI solutions but are slowed by a generative AI skills gap. 90% of APJ respondents said that AI is a priority to their organisation. Today, the top two AI solutions deployed by APJ organisations include virtual assistants/customer support bots (50%), as well as a mix of generative AI solutions (52%). However, when it comes to AI solution implementation, APJ respondents indicate they lack generative AI and prompt engineering skills and require more data scientists and data science skills to support their initiatives.
- Data security and governance are at the forefront of enterprise AI decision-making—not cost. Among respondents, data security, data quality, scalability, and speed of development were the top considerations related to running their AI workloads. Additionally, more than 92% of respondents say that security and reliability are important considerations in their AI strategy. Respondents consistently indicated that data security and governance, including data quality and data protection, are of paramount importance to support AI technologies and services.
- Organisations are more likely to purchase existing AI models or leverage existing open-source AI models (86%) to build their AI applications than to build their own models (5%). This is five points lower than the global average of 10%. This inclination could stem from a confluence of factors, including the substantial costs associated with in-house AI model development, a dearth of skilled AI personnel within the region, and the abundance of readily available pre-trained AI models applicable to diverse purposes.
- 56% of APJ respondents say they plan to improve data movement between cloud, data centre, and edge environments. Furthermore, 55% of APJ respondents said they plan to improve data movement between multiple public clouds.
From Buzzword to Mainstream
“AI is no longer just a buzzword, but a fundamental driver of enterprise evolution and data centre modernisation in 2023 and beyond. While many enterprises have rapidly adopted AI and are reaping the short-term benefits of early adoption, it’s important to remember that AI adoption is a marathon, not a sprint. The adoption strategy will be a key differentiator setting enterprises up for long-term success,” said Aaron White, Vice President and General Manager, APJ Sales, at Nutanix.
“As more enterprises adopt AI applications and workloads, we can expect a new wave of IT infrastructure modernisation initiatives focused on data mobility, security, and protection. Our recent survey has uncovered an important theme among enterprises adopting AI solutions: a growing requirement for data mobility and data protection across data centre, cloud, and edge infrastructure environments. At the heart of this trend is a fundamental understanding among most enterprises regarding the need to explore AI technologies and solutions to maintain a competitive edge,” he added.
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