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AI Creates "Disrupt or Die" Era

"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."

The 2024 Cloud Complexity Report from Netapp 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.

"AI is only as good as the data that fuels it," said Pravjit Tiwana, GM and SVP 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."

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%)

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

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

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.

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.

Methodology: In March 2024, NetApp partnered with Savanta to conduct a quantitative research study of 1,300+ tech and data executives at businesses in 10 markets: US, EMEA (UK, France, Germany, Spain), and APAC (Australia, New Zealand, India, Singapore, Japan).

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AI Creates "Disrupt or Die" Era

"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."

The 2024 Cloud Complexity Report from Netapp 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.

"AI is only as good as the data that fuels it," said Pravjit Tiwana, GM and SVP 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."

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%)

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

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

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.

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.

Methodology: In March 2024, NetApp partnered with Savanta to conduct a quantitative research study of 1,300+ tech and data executives at businesses in 10 markets: US, EMEA (UK, France, Germany, Spain), and APAC (Australia, New Zealand, India, Singapore, Japan).

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...