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Gartner Releases 2012 Hype Cycle for Emerging Technologies

Big data and cloud computing are some of the fastest-moving technologies identified in Gartner Inc.'s 2012 Hype Cycle for Emerging Technologies.

Gartner analysts said that these technologies have moved noticeably along the Hype Cycle since 2011, while consumerization is now expected to reach the Plateau of Productivity in two to five years, down from five to 10 years in 2011.

Bring your own device (BYOD), 3D printing and social analytics are some of the technologies identified at the Peak of Inflated Expectations in this year's Emerging Technologies Hype Cycle.

Gartner's 2012 Hype Cycle Special Report provides strategists and planners with an assessment of the maturity, business benefit and future direction of more than 1,900 technologies, grouped into 92 areas. New Hype Cycles this year include big data, the Internet of Things, in-memory computing and strategic business capabilities.

The Hype Cycle graphic has been used by Gartner since 1995 to highlight the common pattern of overenthusiasm, disillusionment and eventual realism that accompanies each new technology and innovation. The Hype Cycle Special Report is updated annually to track technologies along this cycle and provide guidance on when and where organizations should adopt them for maximum impact and value.

"Gartner's Hype Cycle for Emerging Technologies targets strategic planning, innovation and emerging technology professionals by highlighting a set of technologies that will have broad-ranging impact across the business," said Jackie Fenn, vice president and Gartner fellow. "It is the broadest aggregate Gartner Hype Cycle, featuring technologies that are the focus of attention because of particularly high levels of hype, or those that Gartner believes have the potential for significant impact."

"The theme of this year's Hype Cycle is the concept of 'tipping points.' We are at an interesting moment, a time when many of the scenarios we've been talking about for a long time are almost becoming reality," said Hung LeHong, research vice president at Gartner. "The smarter smartphone is a case in point. It's now possible to look at a smartphone and unlock it via facial recognition, and then talk to it to ask it to find the nearest bank ATM. However, at the same time, we see that the technology is not quite there yet. We might have to remove our glasses for the facial recognition to work, our smartphones don't always understand us when we speak, and the location-sensing technology sometimes has trouble finding us."

Although the Hype Cycle presents technologies individually, Gartner encourages enterprises to consider the technologies in sets or groupings, because so many new capabilities and trends involve multiple technologies working together. Often, one or two technologies that are not quite ready can limit the true potential of what is possible. Gartner refers to these technologies as "tipping point technologies" because, once they mature, the scenario can come together from a technology perspective.

Some of the more significant scenarios, and the tipping point technologies, need to mature so that enterprises and governments can deliver new value and experiences to customers and citizens include:

Any Channel, Any Device, Anywhere — Bring Your Own Everything

The technology industry has long talked about scenarios in which any service or function is available on any device, at anytime and anywhere. This scenario is being fueled by the consumerization trend that is making it acceptable for enterprise employees to bring their own personal devices into the work environment. The technologies and trends featured on this Hype Cycle that are part of this scenario include BYOD, hosted virtual desktops, HTML5, the various forms of cloud computing, silicon anode batteries and media tablets. Although all these technologies and trends need to mature for the scenario to become the norm, HTML 5, hosted virtual networks and silicon anode batteries are particularly strong tipping point candidates.

Smarter Things

A world in which things are smart and connected to the Internet has been in the works for more than a decade. Once connected and made smart, things will help people in every facet of their consumer, citizen and employee lives. There are many enabling technologies and trends required to make this scenario a reality. On the 2012 Hype Cycle, Gartner has included autonomous vehicles, mobile robots, Internet of Things, big data, wireless power, complex-event processing, Internet TV, activity streams, machine-to-machine communication services, mesh networks: sensor, home health monitoring and consumer telematics. The technologies and trends that are the tipping points to success include machine-to-machine communication services, mesh networks: sensor, big data, complex-event processing and activity streams.

Big Data and Global Scale Computing at Small Prices

This broad scenario portrays a world in which analytic insight and computing power are nearly infinite and cost-effectively scalable. Once enterprises gain access to these resources, many improved capabilities are possible, such as better understanding customers or better fraud reduction. The enabling technologies and trends on the 2012 Hype Cycle include quantum computing, the various forms of cloud computing, big data, complex-event processing, social analytics, in-memory database management systems, in-memory analytics, text analytics and predictive analytics. The tipping point technologies that will make this scenario accessible to enterprises, governments and consumers include cloud computing, big data and in-memory database management systems.

The Voice of the Customer Is on File

Humans are social by nature, which drives a need to share — often publicly. This creates a future in which the "voice of customers" is stored somewhere in the cloud and can be accessed and analyzed to provide better insight into them. The 2012 Hype Cycle features the following enabling technologies and trends: automatic content recognition, crowdsourcing, big data, social analytics, activity streams, cloud computing, audio mining/speech analytics and text analytics. Gartner believes that the tipping point technologies are privacy backlash and big data.

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 Releases 2012 Hype Cycle for Emerging Technologies

Big data and cloud computing are some of the fastest-moving technologies identified in Gartner Inc.'s 2012 Hype Cycle for Emerging Technologies.

Gartner analysts said that these technologies have moved noticeably along the Hype Cycle since 2011, while consumerization is now expected to reach the Plateau of Productivity in two to five years, down from five to 10 years in 2011.

Bring your own device (BYOD), 3D printing and social analytics are some of the technologies identified at the Peak of Inflated Expectations in this year's Emerging Technologies Hype Cycle.

Gartner's 2012 Hype Cycle Special Report provides strategists and planners with an assessment of the maturity, business benefit and future direction of more than 1,900 technologies, grouped into 92 areas. New Hype Cycles this year include big data, the Internet of Things, in-memory computing and strategic business capabilities.

The Hype Cycle graphic has been used by Gartner since 1995 to highlight the common pattern of overenthusiasm, disillusionment and eventual realism that accompanies each new technology and innovation. The Hype Cycle Special Report is updated annually to track technologies along this cycle and provide guidance on when and where organizations should adopt them for maximum impact and value.

"Gartner's Hype Cycle for Emerging Technologies targets strategic planning, innovation and emerging technology professionals by highlighting a set of technologies that will have broad-ranging impact across the business," said Jackie Fenn, vice president and Gartner fellow. "It is the broadest aggregate Gartner Hype Cycle, featuring technologies that are the focus of attention because of particularly high levels of hype, or those that Gartner believes have the potential for significant impact."

"The theme of this year's Hype Cycle is the concept of 'tipping points.' We are at an interesting moment, a time when many of the scenarios we've been talking about for a long time are almost becoming reality," said Hung LeHong, research vice president at Gartner. "The smarter smartphone is a case in point. It's now possible to look at a smartphone and unlock it via facial recognition, and then talk to it to ask it to find the nearest bank ATM. However, at the same time, we see that the technology is not quite there yet. We might have to remove our glasses for the facial recognition to work, our smartphones don't always understand us when we speak, and the location-sensing technology sometimes has trouble finding us."

Although the Hype Cycle presents technologies individually, Gartner encourages enterprises to consider the technologies in sets or groupings, because so many new capabilities and trends involve multiple technologies working together. Often, one or two technologies that are not quite ready can limit the true potential of what is possible. Gartner refers to these technologies as "tipping point technologies" because, once they mature, the scenario can come together from a technology perspective.

Some of the more significant scenarios, and the tipping point technologies, need to mature so that enterprises and governments can deliver new value and experiences to customers and citizens include:

Any Channel, Any Device, Anywhere — Bring Your Own Everything

The technology industry has long talked about scenarios in which any service or function is available on any device, at anytime and anywhere. This scenario is being fueled by the consumerization trend that is making it acceptable for enterprise employees to bring their own personal devices into the work environment. The technologies and trends featured on this Hype Cycle that are part of this scenario include BYOD, hosted virtual desktops, HTML5, the various forms of cloud computing, silicon anode batteries and media tablets. Although all these technologies and trends need to mature for the scenario to become the norm, HTML 5, hosted virtual networks and silicon anode batteries are particularly strong tipping point candidates.

Smarter Things

A world in which things are smart and connected to the Internet has been in the works for more than a decade. Once connected and made smart, things will help people in every facet of their consumer, citizen and employee lives. There are many enabling technologies and trends required to make this scenario a reality. On the 2012 Hype Cycle, Gartner has included autonomous vehicles, mobile robots, Internet of Things, big data, wireless power, complex-event processing, Internet TV, activity streams, machine-to-machine communication services, mesh networks: sensor, home health monitoring and consumer telematics. The technologies and trends that are the tipping points to success include machine-to-machine communication services, mesh networks: sensor, big data, complex-event processing and activity streams.

Big Data and Global Scale Computing at Small Prices

This broad scenario portrays a world in which analytic insight and computing power are nearly infinite and cost-effectively scalable. Once enterprises gain access to these resources, many improved capabilities are possible, such as better understanding customers or better fraud reduction. The enabling technologies and trends on the 2012 Hype Cycle include quantum computing, the various forms of cloud computing, big data, complex-event processing, social analytics, in-memory database management systems, in-memory analytics, text analytics and predictive analytics. The tipping point technologies that will make this scenario accessible to enterprises, governments and consumers include cloud computing, big data and in-memory database management systems.

The Voice of the Customer Is on File

Humans are social by nature, which drives a need to share — often publicly. This creates a future in which the "voice of customers" is stored somewhere in the cloud and can be accessed and analyzed to provide better insight into them. The 2012 Hype Cycle features the following enabling technologies and trends: automatic content recognition, crowdsourcing, big data, social analytics, activity streams, cloud computing, audio mining/speech analytics and text analytics. Gartner believes that the tipping point technologies are privacy backlash and big data.

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 ...