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).

Related Links

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The Performance Bottleneck in Enterprise AI Has Been Exposed – Now We Must Fix It

Performance bottlenecks aren't uncommon when it comes to rolling out new technology, regardless of how capable or game-changing that technology might be. Every generation of new tech has encountered roadblocks that had to be overcome before it was truly able to shine. Virtualization forced organizations to rethink resource allocation, cloud transformation had us shift our focus toward scalability and elasticity, and microservices introduced entirely new challenges around observability and distributed systems. There's something different about AI, however ...

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Consider a single order represented across order-management, execution, and settlement systems. Each database, message broker, and application may be online and processing its own records correctly. Yet the workflow has failed if related events arrive on different clocks, rely on inconsistent state, or cannot be reconciled before an operational decision must be made ...

Why AI in IT Is Producing High Productivity but Heavy Workloads

AI now exists in almost every IT workflow. In a recent survey of more than 800 IT service professionals, all respondents indicated the use of AI in some form within their organization. But there's a growing paradox: if dashboards are clearing faster and alerts are resolved at unprecedented speed, why aren't IT service desks reporting lighter workloads? The research found that 71% of IT teams said their actual workload has remained flat or increased since adopting AI. This reality appears to contradict what we’ve been told about AI ...

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Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

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Preparing Network Infrastructure for AI Starts with the Basics

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Agentic Operations Begin with Governed Middleware Access

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...