AI Deployment Trends: NetApp's Cloud Complexity Report Provides Key Findings

AI Deployment Trends: NetApp's Cloud Complexity Report Provides Key Findings

NetApp® released its second annual Cloud Complexity Report. The report analyzes the experiences of global technology decision makers deploying AI at scale and shows a stark contrast between AI leaders and AI laggards. This year's report provides global insights into the progress, readiness, challenges, and momentum since last year's report, what we can learn from both the AI leaders and AI laggards, and the critical role of a unified data infrastructure in achieving AI success.

"AI is only as good as the data that fuels it," said Pravjit Tiwana, General Manager and Senior Vice President of Cloud Storage at NetApp. "Both the AI leaders and AI laggards show us that in the prevailing hybrid IT environment, the more unified and reliable your data, the more likely your AI initiatives are to be successful."

"APAC leaders today recognize the efficiency and innovation gains offered by AI; however, the data shows adoption variations between industries and geographies in the region," said Matthew Swinbourne, CTO Cloud Architecture at NetApp Asia Pacific. "Whether companies are AI leaders or AI laggards, optimizing IT environments before deploying AI must be top of mind to see the best return from investment."

There is a Significant Divide Between AI Leaders and AI Laggards

The report found a clear divide between AI leaders and AI laggards across several areas including:

·         Regions: 60% of AI-leading countries (India, Singapore, UK, USA) have AI projects up and running or in pilot, in stark contrast to 36% in AI-lagging countries (Spain, Australia/New Zealand, Germany, Japan).

·         Industries: Technology leads with 70% of AI projects up and running or in pilot, while Banking & Financial Services and Manufacturing follow with 55% and 50%, respectively. However, Healthcare (38%) and Media & Entertainment (25%) are trailing.

·         Company size: Larger companies (with more than 250 employees) are more likely to have AI projects in motion, with 62% reporting projects up and running or in pilot, versus 36% of smaller companies (with fewer than 250 employees).

Both AI leaders and AI laggards show a difference in their approach to AI:

·         Globally, 67% of companies in AI-leading countries report having hybrid IT environments, with India leading (70%) and Japan lagging (24%).

·         AI leaders are also more likely to report benefits from AI, including a 50% increase in production rates, 46% in the automation of routine activities, and a 45% improvement in customer experience.

"The rise of AI is ushering in a new disrupt-or-die era," said Gabie Boko, Chief Marketing Officer at NetApp. "Data-ready enterprises that connect and unify broad structured and unstructured data sets into an intelligent data infrastructure are best positioned to win in the age of AI."

AI Laggards Must Swiftly Innovate to Stay Competitive

Despite the divide, there is notable progress among AI laggards in preparing their IT environments for AI, but the window to catch up is closing rapidly.

·         A significant number of companies in AI-lagging countries (42%) have optimized their IT environments for AI, including Germany (67%) and Spain (59%). ANZ and Japan, however, are below the global average at 38% and 25%, respectively.

·         Companies in some AI-lagging countries already report seeing the benefits of a unified data infrastructure in place, such as:

o   Easier data sharing: Spain (45%), Australia/New Zealand (43%), Germany (44%)

o   Increased visibility: Spain (54%) and Germany (46%)


IT Costs and Data Security Emerge as Top Challenges but Won't Impede AI Progress


Rising IT costs and ensuring data security are the two of the biggest challenges in the AI era, but they will not block AI progress. Instead, AI leaders will scale back, cut other IT operations, or reallocate costs from other parts of the business to fund AI initiatives.

·         AI leaders will also increase their cloud operations (CloudOps), data security and AI investments throughout 2024, with 40% of large companies saying AI projects have already increased IT costs.

·         Year over year, "increased cybersecurity risk" jumped 16% as a top concern from 45% to 61%, while all other concerns decreased.

·         To manage AI project costs, 31% of companies globally are reallocating funds from other business areas, with India (48%), UK (40%), and US (35%) leading this trend.

In APAC, 34% of companies said AI projects have already increased IT costs. 60% of respondents cited "increased cybersecurity risk" as their top concern, while 31% said they are reallocating funds from other business areas to manage AI project costs.

Security, AI, and CloudOps Drive 2024 Cloud Investments

As global companies, whether AI leaders or AI laggards, increase investments, they are relying on the cloud to support their goals.

  • Companies reported that they expect to increase AI-driven cloud deployments by 19% from 2024 to 2030.

  • 85% of AI leaders plan to enhance their CloudOps automation over the next year.

  • Increasing data security investments is a global priority, jumping 25% from 33% in 2023 to 58% in 2024.

  • In APAC, the proportion of companies which will have more than 50% of their cloud deployments supported by AI-driven applications will increase 15% between 2024 and 2030. Two-thirds (67%) of AI leaders here plan to enhance their CloudOps automation over the next year, while data security investments are expected to jump 21% from 37% in 2023 to 58% in 2024.

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