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AI Drives New Wave of Digital Transformation

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink.

Similar majorities agreed that their organization's success over the next three years will be highly contingent on their ability to effectively deploy AI (94%) and the emergence of AI would require them to invest in more tailored digital adoption support than they can currently provide (94%).

The research found deep concerns among IT leaders around whether their coworkers have the digital dexterity needed to adapt to the AI era. In particular:

  • 96% said that they would need to enhance their digital adoption support to help employees adapt to AI.
  • 88% agreed that users were more likely to be daunted by new technologies such as generative AI.
  • 92% believe that digital friction is going to increase in the coming years.
  • On average, IT leaders believe that less than half (47%) of employees have the requisite digital dexterity to adapt to inbound technological changes.

"The AI era is going to be a radical break from previous waves of digital transformation," said Vedant Sampath, CTO at Nexthink. "Unlocking the potential of AI is going to be the competitive differentiator of the next decade, but this research shows that businesses face a huge challenge in upskilling their employees to meet the moment. Otherwise, executives risk finding themselves having spent millions of dollars on software and IT services that are just gathering dust."

Respondents were almost unanimous in their view that AI is set to transform the way their business operates (96%), and that digital dexterity will be integral to organizational success in the near future (95%), while a large majority (82%) also reported that failing to appropriately invest in AI would result in them falling behind competitors.

However, there is broad awareness that realizing ROI on such investments may be difficult, with 93% acknowledging that they need to improve their ability to identify underperforming digital investments while 91% feel that it will be necessary to invest in AI tools specifically to monitor and enable adoption of other AI tools.

"Managing the transition to the AI era is going to require businesses to be smart around digital adoption," added Sampath. "Having application owners act as knowledge gatekeepers is neither efficient nor scalable. Instead, businesses need to provide employees with timely context-relevant assistance for the task they are performing, in addition to application monitoring, and real-time resolution when issues occur."

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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 ...

AI Drives New Wave of Digital Transformation

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink.

Similar majorities agreed that their organization's success over the next three years will be highly contingent on their ability to effectively deploy AI (94%) and the emergence of AI would require them to invest in more tailored digital adoption support than they can currently provide (94%).

The research found deep concerns among IT leaders around whether their coworkers have the digital dexterity needed to adapt to the AI era. In particular:

  • 96% said that they would need to enhance their digital adoption support to help employees adapt to AI.
  • 88% agreed that users were more likely to be daunted by new technologies such as generative AI.
  • 92% believe that digital friction is going to increase in the coming years.
  • On average, IT leaders believe that less than half (47%) of employees have the requisite digital dexterity to adapt to inbound technological changes.

"The AI era is going to be a radical break from previous waves of digital transformation," said Vedant Sampath, CTO at Nexthink. "Unlocking the potential of AI is going to be the competitive differentiator of the next decade, but this research shows that businesses face a huge challenge in upskilling their employees to meet the moment. Otherwise, executives risk finding themselves having spent millions of dollars on software and IT services that are just gathering dust."

Respondents were almost unanimous in their view that AI is set to transform the way their business operates (96%), and that digital dexterity will be integral to organizational success in the near future (95%), while a large majority (82%) also reported that failing to appropriately invest in AI would result in them falling behind competitors.

However, there is broad awareness that realizing ROI on such investments may be difficult, with 93% acknowledging that they need to improve their ability to identify underperforming digital investments while 91% feel that it will be necessary to invest in AI tools specifically to monitor and enable adoption of other AI tools.

"Managing the transition to the AI era is going to require businesses to be smart around digital adoption," added Sampath. "Having application owners act as knowledge gatekeepers is neither efficient nor scalable. Instead, businesses need to provide employees with timely context-relevant assistance for the task they are performing, in addition to application monitoring, and real-time resolution when issues occur."

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 ...