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Gartner: Top Predictions for IT in 2017 and Beyond

Gartner revealed its top predictions for 2017 and beyond, examining three fundamental effects of continued digital innovation: experience and engagement, business innovation, and the secondary effects that result from increased digital capabilities.

"Gartner's top strategic predictions continue to offer a provocative look at what might happen in some of the most critical areas of technology evolution. At the core of future outcomes is the notion of digital disruption, which has moved from an infrequent inconvenience to a consistent stream of change that is redefining markets and entire industries," said Daryl Plummer, Managing VP, Chief of Research and Gartner Fellow. "Last year, we said digital changes were coming fast. This year the acceleration continues and may cause secondary effects that have wide-ranging impact on people and technology."

By 2020, 100 million consumers will shop in augmented reality

The popularity of augmented reality (AR) applications, such as Pokémon GO, will help bring AR into the mainstream, prompting more retailers to incorporate it into the shopping experience. As mobile device usage becomes an ingrained behavior, further blurring the lines between the physical and digital worlds, brands and their retail partners will need to develop mechanisms to leverage this behavior to enhance the shopping experience. Using AR applications to layer digital information — text, images, video and audio — on top of the physical world, represents one such route to deeper engagement, both in-store and in other locations. For example, a consumer pointing the IKEA catalog app at a room in his home can "place" furniture where he'd like it to go. This real-world element differentiates AR apps from those offering virtual reality (VR).

By 2019, 20 percent of brands will abandon their mobile apps

Many brands are finding that the level of adoption, customer engagement and return on investment (ROI) delivered by their mobile applications are significantly less than the expectations that underpinned their app investment. New approaches are emerging that have a lower barrier to discovery and install, and offer levels of engagement that approach those of applications at a fraction of the investment, support and marketing cost. Many companies will evaluate these experiences against their under-performing applications and opt to reduce their losses by allowing their apps to expire.

By 2020, algorithms will positively alter the behavior of more than 1 billion global workers

Contextualization algorithms have advanced exponentially to include a variety of behavioral interventions such as psychology, social neuroscience and cognitive science. Human beings tend to be emotionally charged and factually drained, causing them to be irrational. Algorithms can positively alter that behavior by augmenting their intelligence with the large collective memory bank containing knowledge that has been socialized and put to the test. This will help workers "remember" anything or be informed of just-in-time knowledge that they have never even experienced, leaving them to objectively complete the task at hand but also to better appreciate life as it unveils. Use of algorithms can raise alarms of "creepiness," however, when used to effect positive outcomes, it can bring about changes to multiple industries.

By 2022, a blockchain-based business will be worth $10 billion

Blockchain technology is established as the next revolution in transaction recording. A blockchain ledger provides an immutable, shared view of all transactions between engaging parties. Parties can therefore immediately act on a committed blockchain record, secure in the knowledge that it cannot be changed. Any kind of value exchange can happen in minutes, not days. Blockchain applications can free up cash, reduce transaction costs, and accelerate business processes. While blockchain development is still immature, it is attracting product and capital investment.

By 2021, 20 percent of all activities an individual engages in will involve at least one the top-seven digital giants

The current top-seven digital giants by revenue and market capitalization are Google, Apple, Facebook, Amazon, Baidu, Alibaba and Tencent. As the physical, financial and healthcare world becomes more digital, many of the activities an individual engages in will be connected. This convergence means that any activity could include one of the digital giants. Mobile apps, payment, smart agents (e.g., Amazon Alexa), and digital ecosystems (e.g., Apple HomeKit, WeChat Utility and City Services) will make the digital giants part of many of the activities we do.

Through 2019, every $1 enterprises invest in innovation will require an additional $7 in core execution

For many enterprise, adopting a bimodal IT style to jump-start innovation has been a priority and critical first step. Close alignment of Mode 1 and 2 teams is crucial to the realization of the digital business goals. Unfortunately, the deployment costs of the Mode 2 "ideated solution" are not necessarily considered during ideation, and for most, the Mode 1 costs are not factored into the initial funding. Designing, implementing, integrating, operationalizing, and managing the ideated solution can be significantly more than the initial innovation costs. Thus, Gartner anticipates that for every $1 spent on the digital innovation/ideation phase, enterprises will spend on average $7 for deploying the solution.

Through 2020, IoT will increase data center storage demand by less than 3 percent

The Internet of Things (IoT) has enormous potential for data generation across the roughly 21 billion endpoints expected to be in use in 2020. Of the roughly 900 exabytes worth of data center hard-disk drive (HDD) and solid-state drive (SSD) capacity forecast to ship in 2020, IoT discrete sensor storage will represent only 0.4 percent, with storage from multimedia sensors consuming another 2 percent, for a rounded total of 2.3 percent. This indicates that IoT can scale and deliver important data-driven business value and insight, while remaining manageable from a storage infrastructure standpoint.

Top Recommendations to Ensure Performance for the IoT

By 2022, IoT will save consumers and businesses $1 trillion a year in maintenance, services and consumables

The IoT holds enormous promise in reducing the cost of maintenance and consumables. The challenge lies in providing a secure, robust implementation that can deliver savings over one or two decades, without driving management costs that absorb any savings made. This could be an inexpensive monitoring system based on simple sensors that report defining characteristics to analytical servers. The analytics are used to spot patterns in the fleet data, and recommend maintenance based on actual usage and condition, not based on elapsed time or estimated condition. At the other extreme, there is the rise of the digital twin. The digital twin captures near real-time data feeds from its sensor-enhanced real-world twin, and uses this along with other data sources (e.g., weather, historian data, algorithms, smart machine analysis) to update its simulation to reflect the physical state of the twin.

By 2020, 40 percent of employees can cut their healthcare costs by wearing a fitness tracker

Companies will increasingly appoint fitness program managers to work closely with human resource leaders to include fitness trackers in wellness programs as part of a broader employee engagement initiative. Healthcare providers can save lives and downstream costs by acting on the data from wearable fitness trackers that show health risks to the user. Wearables provide a wealth of data to be analyzed either in real-time or in retrospect with the potential for doctors and other healthcare professionals to have access to both contextual and historical information, if the patient agrees to share it.

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: Top Predictions for IT in 2017 and Beyond

Gartner revealed its top predictions for 2017 and beyond, examining three fundamental effects of continued digital innovation: experience and engagement, business innovation, and the secondary effects that result from increased digital capabilities.

"Gartner's top strategic predictions continue to offer a provocative look at what might happen in some of the most critical areas of technology evolution. At the core of future outcomes is the notion of digital disruption, which has moved from an infrequent inconvenience to a consistent stream of change that is redefining markets and entire industries," said Daryl Plummer, Managing VP, Chief of Research and Gartner Fellow. "Last year, we said digital changes were coming fast. This year the acceleration continues and may cause secondary effects that have wide-ranging impact on people and technology."

By 2020, 100 million consumers will shop in augmented reality

The popularity of augmented reality (AR) applications, such as Pokémon GO, will help bring AR into the mainstream, prompting more retailers to incorporate it into the shopping experience. As mobile device usage becomes an ingrained behavior, further blurring the lines between the physical and digital worlds, brands and their retail partners will need to develop mechanisms to leverage this behavior to enhance the shopping experience. Using AR applications to layer digital information — text, images, video and audio — on top of the physical world, represents one such route to deeper engagement, both in-store and in other locations. For example, a consumer pointing the IKEA catalog app at a room in his home can "place" furniture where he'd like it to go. This real-world element differentiates AR apps from those offering virtual reality (VR).

By 2019, 20 percent of brands will abandon their mobile apps

Many brands are finding that the level of adoption, customer engagement and return on investment (ROI) delivered by their mobile applications are significantly less than the expectations that underpinned their app investment. New approaches are emerging that have a lower barrier to discovery and install, and offer levels of engagement that approach those of applications at a fraction of the investment, support and marketing cost. Many companies will evaluate these experiences against their under-performing applications and opt to reduce their losses by allowing their apps to expire.

By 2020, algorithms will positively alter the behavior of more than 1 billion global workers

Contextualization algorithms have advanced exponentially to include a variety of behavioral interventions such as psychology, social neuroscience and cognitive science. Human beings tend to be emotionally charged and factually drained, causing them to be irrational. Algorithms can positively alter that behavior by augmenting their intelligence with the large collective memory bank containing knowledge that has been socialized and put to the test. This will help workers "remember" anything or be informed of just-in-time knowledge that they have never even experienced, leaving them to objectively complete the task at hand but also to better appreciate life as it unveils. Use of algorithms can raise alarms of "creepiness," however, when used to effect positive outcomes, it can bring about changes to multiple industries.

By 2022, a blockchain-based business will be worth $10 billion

Blockchain technology is established as the next revolution in transaction recording. A blockchain ledger provides an immutable, shared view of all transactions between engaging parties. Parties can therefore immediately act on a committed blockchain record, secure in the knowledge that it cannot be changed. Any kind of value exchange can happen in minutes, not days. Blockchain applications can free up cash, reduce transaction costs, and accelerate business processes. While blockchain development is still immature, it is attracting product and capital investment.

By 2021, 20 percent of all activities an individual engages in will involve at least one the top-seven digital giants

The current top-seven digital giants by revenue and market capitalization are Google, Apple, Facebook, Amazon, Baidu, Alibaba and Tencent. As the physical, financial and healthcare world becomes more digital, many of the activities an individual engages in will be connected. This convergence means that any activity could include one of the digital giants. Mobile apps, payment, smart agents (e.g., Amazon Alexa), and digital ecosystems (e.g., Apple HomeKit, WeChat Utility and City Services) will make the digital giants part of many of the activities we do.

Through 2019, every $1 enterprises invest in innovation will require an additional $7 in core execution

For many enterprise, adopting a bimodal IT style to jump-start innovation has been a priority and critical first step. Close alignment of Mode 1 and 2 teams is crucial to the realization of the digital business goals. Unfortunately, the deployment costs of the Mode 2 "ideated solution" are not necessarily considered during ideation, and for most, the Mode 1 costs are not factored into the initial funding. Designing, implementing, integrating, operationalizing, and managing the ideated solution can be significantly more than the initial innovation costs. Thus, Gartner anticipates that for every $1 spent on the digital innovation/ideation phase, enterprises will spend on average $7 for deploying the solution.

Through 2020, IoT will increase data center storage demand by less than 3 percent

The Internet of Things (IoT) has enormous potential for data generation across the roughly 21 billion endpoints expected to be in use in 2020. Of the roughly 900 exabytes worth of data center hard-disk drive (HDD) and solid-state drive (SSD) capacity forecast to ship in 2020, IoT discrete sensor storage will represent only 0.4 percent, with storage from multimedia sensors consuming another 2 percent, for a rounded total of 2.3 percent. This indicates that IoT can scale and deliver important data-driven business value and insight, while remaining manageable from a storage infrastructure standpoint.

Top Recommendations to Ensure Performance for the IoT

By 2022, IoT will save consumers and businesses $1 trillion a year in maintenance, services and consumables

The IoT holds enormous promise in reducing the cost of maintenance and consumables. The challenge lies in providing a secure, robust implementation that can deliver savings over one or two decades, without driving management costs that absorb any savings made. This could be an inexpensive monitoring system based on simple sensors that report defining characteristics to analytical servers. The analytics are used to spot patterns in the fleet data, and recommend maintenance based on actual usage and condition, not based on elapsed time or estimated condition. At the other extreme, there is the rise of the digital twin. The digital twin captures near real-time data feeds from its sensor-enhanced real-world twin, and uses this along with other data sources (e.g., weather, historian data, algorithms, smart machine analysis) to update its simulation to reflect the physical state of the twin.

By 2020, 40 percent of employees can cut their healthcare costs by wearing a fitness tracker

Companies will increasingly appoint fitness program managers to work closely with human resource leaders to include fitness trackers in wellness programs as part of a broader employee engagement initiative. Healthcare providers can save lives and downstream costs by acting on the data from wearable fitness trackers that show health risks to the user. Wearables provide a wealth of data to be analyzed either in real-time or in retrospect with the potential for doctors and other healthcare professionals to have access to both contextual and historical information, if the patient agrees to share it.

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 ...