44% of respondents choose to purchase pre-existing AI models, whereas 5% plan to build their own models for AI applications.
Nutanix, a hybrid multi-cloud computing company, released the Nutanix State of Enterprise AI Report for Asia-Pacific and Japan (APJ) at its .NEXT on Tour event in Mumbai. The report highlights enterprise AI deployment and trends, as well as how planned implementations will affect staffing, IT, and cloud investments in the year ahead. It also indicates that AI could be a priority for 90% of APJ organizations and that most are planning investments to support it – whether to modernize their IT infrastructure (84%) or to advance their edge strategy (81%).
Key findings include:
- 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 organization. Today, the top two AI solutions deployed by APJ organizations include virtual assistants/customer support bots (50%) and a mix of generative AI solutions (52%). However, APJ respondents indicate they lack generative AI and prompt engineering skills when it comes to AI solution implementation. They also require more data scientists and data science skills to support their initiatives.
- Today, data security and governance are at the forefront of enterprise AI decision-making – not cost. Data security, quality, scalability, and development speed among respondents were the top considerations for running their AI workloads. Additionally, more than 92% of respondents say that security and reliability are essential considerations in their AI strategy. Respondents consistently indicated that data security and governance, including data quality and protection, are paramount to support AI technologies and services. This may create a windfall for related IT infrastructure markets – specifically for data storage, security, governance, and protection – as new and growing AI technology budgets are allocated to these essential functions.
- Organizations 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 center, and edge environments. Furthermore, 55% of APJ respondents said they plan to improve data movement between multiple public clouds.
“AI is no longer just a buzzword, but a fundamental driver of enterprise evolution and data center modernization 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. As more enterprises adopt AI applications and workloads, we can expect a new wave of IT infrastructure modernization 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 center, 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.” said Aaron White, vice president and general manager, APJ Sales, Nutanix.