Skip to main content

Gartner Says Two-Thirds of Enterprises Will Adopt Mobile Device Management for Corporate Liable Users Through 2017

Over the next five years, 65 percent of enterprises will adopt a mobile device management (MDM) solution for their corporate liable users, according to Gartner, Inc.

With the increased functionality of smartphones, and the increasing popularity of tablets, much of the network traffic and corporate data that was once the primary domain of enterprise PCs is now being shifted to mobile devices.

"The era of the PC has ended. Employees are becoming more mobile and looking for ways to still be connected wherever work needs to be done," said Phil Redman, research vice president at Gartner. "The convenience and productivity gains that mobile devices bring are too tempting for most companies and their employees. Securing corporate data on mobile devices is a big challenge, but one that companies must embrace. Enterprises are struggling with how to support and secure this dynamic workforce."

Gartner predicts that through 2017, 90 percent of enterprises will have two or more mobile operating systems to support. In the past year, many companies have moved to Apple's iOS as their main mobile device platform, with others to follow over the next 12 to 18 months. As enterprises continue to offer multiplatform support, and new platforms — such as Windows 8 — continue to emerge, MDM needs will continue to grow.

As one of the fastest-growing enterprise devices in the past 18 months, tablets are a further driving force for enterprises adopting MDM. Most companies and users are supporting the tablet for limited usage, typically for email and personal information management (PIM) functions. However, users are pushing for more enterprise applications to be supported on the tablet, usually through either enterprise or application provider development. As more of these native apps become available, and as remote access technology improves, more enterprise content will be stored on these devices. Users are already synchronizing corporate content into public clouds for later retrieval on the devices.

"The rapid influx of users bringing their own consumer mobile devices that demand access to corporate resources presents challenges to organizations," said Redman. "However, by implementing a structured support system with varied support levels, IT organizations can shield business information and enforce policies about data movement between the device and the corporate network, while enabling users to adopt the device they deem most appropriate. Organizations will find it hard to achieve an efficient mobile-support system if all platforms are not managed the same way under enterprise requirements. Like PCs, mobile devices are forms of client access devices, and the policies for them should be similar in strength but optimized for mobile usage, to those governing PCs."

Gartner believes that mobile device proliferation is inevitable and the only way that IT staff can maintain control is by separating mobile computing devices into three distinct device classes:

- trusted standard devices provided by the company

- tolerated devices

- non-supported devices

In this scenario, users are given a predefined list of supported technologies in each class, along with a budget for the projected amount that each selection consumes. Users can optimize the technologies according to their requirements without exceeding the budget. Expense limits and spending caps by individuals bypass the need to rely on subjective interpretations of "reasonable use."

"This is just the start for MDM. More data is being put on mobile devices, and enterprises are fast developing their own applications to support their mobile users. As mobile devices continue to displace traditional PCs, enterprises will look to their existing MDM systems to support more devices and enterprise applications and data," said Redman. "MDM vendors are moving beyond security, to support enterprise and third-party applications, data and content. In the next two years, we will continue to see MDM platforms broaden out and become more enterprise mobile system management platforms, not just for devices alone."

Hot Topic

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 Says Two-Thirds of Enterprises Will Adopt Mobile Device Management for Corporate Liable Users Through 2017

Over the next five years, 65 percent of enterprises will adopt a mobile device management (MDM) solution for their corporate liable users, according to Gartner, Inc.

With the increased functionality of smartphones, and the increasing popularity of tablets, much of the network traffic and corporate data that was once the primary domain of enterprise PCs is now being shifted to mobile devices.

"The era of the PC has ended. Employees are becoming more mobile and looking for ways to still be connected wherever work needs to be done," said Phil Redman, research vice president at Gartner. "The convenience and productivity gains that mobile devices bring are too tempting for most companies and their employees. Securing corporate data on mobile devices is a big challenge, but one that companies must embrace. Enterprises are struggling with how to support and secure this dynamic workforce."

Gartner predicts that through 2017, 90 percent of enterprises will have two or more mobile operating systems to support. In the past year, many companies have moved to Apple's iOS as their main mobile device platform, with others to follow over the next 12 to 18 months. As enterprises continue to offer multiplatform support, and new platforms — such as Windows 8 — continue to emerge, MDM needs will continue to grow.

As one of the fastest-growing enterprise devices in the past 18 months, tablets are a further driving force for enterprises adopting MDM. Most companies and users are supporting the tablet for limited usage, typically for email and personal information management (PIM) functions. However, users are pushing for more enterprise applications to be supported on the tablet, usually through either enterprise or application provider development. As more of these native apps become available, and as remote access technology improves, more enterprise content will be stored on these devices. Users are already synchronizing corporate content into public clouds for later retrieval on the devices.

"The rapid influx of users bringing their own consumer mobile devices that demand access to corporate resources presents challenges to organizations," said Redman. "However, by implementing a structured support system with varied support levels, IT organizations can shield business information and enforce policies about data movement between the device and the corporate network, while enabling users to adopt the device they deem most appropriate. Organizations will find it hard to achieve an efficient mobile-support system if all platforms are not managed the same way under enterprise requirements. Like PCs, mobile devices are forms of client access devices, and the policies for them should be similar in strength but optimized for mobile usage, to those governing PCs."

Gartner believes that mobile device proliferation is inevitable and the only way that IT staff can maintain control is by separating mobile computing devices into three distinct device classes:

- trusted standard devices provided by the company

- tolerated devices

- non-supported devices

In this scenario, users are given a predefined list of supported technologies in each class, along with a budget for the projected amount that each selection consumes. Users can optimize the technologies according to their requirements without exceeding the budget. Expense limits and spending caps by individuals bypass the need to rely on subjective interpretations of "reasonable use."

"This is just the start for MDM. More data is being put on mobile devices, and enterprises are fast developing their own applications to support their mobile users. As mobile devices continue to displace traditional PCs, enterprises will look to their existing MDM systems to support more devices and enterprise applications and data," said Redman. "MDM vendors are moving beyond security, to support enterprise and third-party applications, data and content. In the next two years, we will continue to see MDM platforms broaden out and become more enterprise mobile system management platforms, not just for devices alone."

Hot Topic

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 ...