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AI and ML: Top Strategic Enterprise IT Investment Priorities in 2018

AI (Artificial Intelligence) and ML (Machine Learning) are the number one strategic enterprise IT investment priority in 2018 (named by 33% of enterprises), taking the top spot from container management (28%), and clearly leaving behind DevOps pipeline automation (13%), according to new Enterprise Management Associates (EMA) research.

At the same time, most enterprises are still struggling to understand the basics of how to successfully evaluate AI and ML solutions, how to put project performance metrics in place, and how to handle the eight key limitations of AI and ML technologies today, says EMA.

Some of the key benefits of artificial intelligence and machine learning identified in the research are:

■ Free up 30% of developer time and up to 50% of IT operator time used to support infrastructure

■ Eliminate operational silos as the root cause of cost, quality, and speed bottlenecks in DevOps

■ Proactively address operational issues and minimize mean time to repair (MTTR)

■ Curb alert flood and receive earlier alerts aligned with business priorities

■ Help the 72% of enterprises with ungoverned Kubernetes clusters to bring these back under corporate control

■ Operate a mostly self-driving hybrid cloud to unlock the 50% of data that cannot go into the public cloud today

■ Improve collaboration between developers, IT, and business

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Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

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Poor DEX directly costs global businesses an average of 470,000 hours per year, equivalent to around 226 full-time employees, according to a new report from Nexthink, Cracking the DEX Equation: The Annual Workplace Productivity Report. This indicates that digital friction is a vital and underreported element of the global productivity crisis ...

AI and ML: Top Strategic Enterprise IT Investment Priorities in 2018

AI (Artificial Intelligence) and ML (Machine Learning) are the number one strategic enterprise IT investment priority in 2018 (named by 33% of enterprises), taking the top spot from container management (28%), and clearly leaving behind DevOps pipeline automation (13%), according to new Enterprise Management Associates (EMA) research.

At the same time, most enterprises are still struggling to understand the basics of how to successfully evaluate AI and ML solutions, how to put project performance metrics in place, and how to handle the eight key limitations of AI and ML technologies today, says EMA.

Some of the key benefits of artificial intelligence and machine learning identified in the research are:

■ Free up 30% of developer time and up to 50% of IT operator time used to support infrastructure

■ Eliminate operational silos as the root cause of cost, quality, and speed bottlenecks in DevOps

■ Proactively address operational issues and minimize mean time to repair (MTTR)

■ Curb alert flood and receive earlier alerts aligned with business priorities

■ Help the 72% of enterprises with ungoverned Kubernetes clusters to bring these back under corporate control

■ Operate a mostly self-driving hybrid cloud to unlock the 50% of data that cannot go into the public cloud today

■ Improve collaboration between developers, IT, and business

Hot Topics

The Latest

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

Artificial Intelligence (AI) is reshaping observability, and observability is becoming essential for AI. This is a two-way relationship that is increasingly relevant as enterprises scale generative AI ... This dual role makes AI and observability inseparable. In this blog, I cover more details of each side ...

Poor DEX directly costs global businesses an average of 470,000 hours per year, equivalent to around 226 full-time employees, according to a new report from Nexthink, Cracking the DEX Equation: The Annual Workplace Productivity Report. This indicates that digital friction is a vital and underreported element of the global productivity crisis ...