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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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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Alert Fatigue Is No Longer a Morale Problem, It's a Reliability Risk and a System Failure

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Most Enterprises Think They Can Switch AI Vendors in a Month ... Most Who've Tried Couldn't

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Your Observability Stack Has a Telemetry Pipeline Problem

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

Operator to Orchestrator: 80% of IT Pros See Shift in Role as AI Permeates Workflows

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

Gartner: 40% of Organizations Deploying AI Will Use AI Observability to Monitor Model Performance by 2028

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Almost Half of AI-Generated Code Fails in Production

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

AI Requires Design, Not Edicts

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

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Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

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Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...