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Gartner: Everyday AI and Digital Employee Experience Are 2 Years Away from Mainstream Adoption

Everyday AI and digital employee experience (DEX) are projected to reach mainstream adoption in less than two years according to the Gartner, Inc. Hype Cycle for Digital Workplace Applications, 2024.

"Everyday AI promises to remove digital friction, by helping employees write, research, collaborate and ideate," said Matt Cain, Distinguished VP Analyst at Gartner. "It is a core part of DEX, which is a concentrated effort to remove digital friction and improve workforce digital dexterity, which itself is one of the key factors that will drive organizational prosperity through 2030."

2024 has been a critical year for digital workplace application leaders, as the focus on hybrid and remote work dwindles and the need for a strategic concentration on everyday AI rises. Everyday AI is placed on the Peak of Inflated Expectations on the Gartner Hype Cycle for Digital Workplace Applications, 2024.

"Everyday AI technology aims to help employees deliver work with speed, comprehensiveness and confidence," said Adam Preset, VP Analyst at Gartner. "It supports a new way of working, where intelligent software is acting as more of a collaborator than a tool. The digital workplace is now entering the era of everyday AI."

As technology vendors seek ways to improve productivity among workers that go beyond traditional application and feature enhancements, they can look towards everyday AI. This technology not only delivers productivity benefits, but also provides new marketable offerings such as tools to help workers find and synthesize relevant information, answer questions more comprehensively and produce work artifacts more easily.

"Everyday AI will become more sophisticated, moving from services that, for example, can sort and summarize chats and email messages to services that can write a report with minimal guidance," said Preset. "In many ways, everyday AI is the future of workforce productivity."

Increased Emphasis on Organizations to Have a DEX Strategy

Nearly all employees are becoming digital employees as they spend more time working with technology than ever before. Because of this, organizations must have a strategy to measure and improve DEX to attract and retain talent to improve employee engagement and maximize discretionary effort and intent-to-stay.

Business leaders are looking for guidance on how technology can help boost productivity and organizational alignment. DEX emphasizes best practices that boost digital dexterity, attract and retain talent, and help employees deliver against business outcomes.

DEX is in the Trough of Disillusionment on the Hype Cycle, meaning that interest is waning as experiments and implementations fail to deliver. To increase the appeal and relevance around DEX, business leaders should take a holistic approach across IT and non-IT partners to build a meaningful environment that empowers employees to adopt new ways of working.

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Gartner: Everyday AI and Digital Employee Experience Are 2 Years Away from Mainstream Adoption

Everyday AI and digital employee experience (DEX) are projected to reach mainstream adoption in less than two years according to the Gartner, Inc. Hype Cycle for Digital Workplace Applications, 2024.

"Everyday AI promises to remove digital friction, by helping employees write, research, collaborate and ideate," said Matt Cain, Distinguished VP Analyst at Gartner. "It is a core part of DEX, which is a concentrated effort to remove digital friction and improve workforce digital dexterity, which itself is one of the key factors that will drive organizational prosperity through 2030."

2024 has been a critical year for digital workplace application leaders, as the focus on hybrid and remote work dwindles and the need for a strategic concentration on everyday AI rises. Everyday AI is placed on the Peak of Inflated Expectations on the Gartner Hype Cycle for Digital Workplace Applications, 2024.

"Everyday AI technology aims to help employees deliver work with speed, comprehensiveness and confidence," said Adam Preset, VP Analyst at Gartner. "It supports a new way of working, where intelligent software is acting as more of a collaborator than a tool. The digital workplace is now entering the era of everyday AI."

As technology vendors seek ways to improve productivity among workers that go beyond traditional application and feature enhancements, they can look towards everyday AI. This technology not only delivers productivity benefits, but also provides new marketable offerings such as tools to help workers find and synthesize relevant information, answer questions more comprehensively and produce work artifacts more easily.

"Everyday AI will become more sophisticated, moving from services that, for example, can sort and summarize chats and email messages to services that can write a report with minimal guidance," said Preset. "In many ways, everyday AI is the future of workforce productivity."

Increased Emphasis on Organizations to Have a DEX Strategy

Nearly all employees are becoming digital employees as they spend more time working with technology than ever before. Because of this, organizations must have a strategy to measure and improve DEX to attract and retain talent to improve employee engagement and maximize discretionary effort and intent-to-stay.

Business leaders are looking for guidance on how technology can help boost productivity and organizational alignment. DEX emphasizes best practices that boost digital dexterity, attract and retain talent, and help employees deliver against business outcomes.

DEX is in the Trough of Disillusionment on the Hype Cycle, meaning that interest is waning as experiments and implementations fail to deliver. To increase the appeal and relevance around DEX, business leaders should take a holistic approach across IT and non-IT partners to build a meaningful environment that empowers employees to adopt new ways of working.

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...