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).

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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

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Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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