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How IT Departments Are Successfully Adopting Artificial Intelligence Technologies

Patricia Diaz-Hymes

We all know artificial intelligence (AI) is a hot topic — but beyond the buzzword, have you ever wondered how IT departments are actually adopting AI technologies to improve on their operations?

Because the term "AI" gets thrown around a lot, let's start with what it means. Given all the marketing hype this technology has been given, I often find myself debating with peers on what AI actually is. Understanding that many vendors have usurped some loose sense of the term in order to claim AI functionality, let's be factual in terms of what it is. As Gartner defines it, artificial intelligence is:

"Technology that appears to emulate human performance typically by learning, coming to its own conclusions, appearing to understand complex content, engaging in natural dialogs with people, enhancing human cognitive performance (also known as cognitive computing) or replacing people on execution of nonroutine tasks. Applications include autonomous vehicles, automatic speech recognition and generation and detecting novel concepts and abstractions (useful for detecting potential new risks and aiding humans quickly understand very large bodies of ever-changing information)."

46% of the companies surveyed said their IT departments are using AI

Use cases for understanding AI as technology that emulates human performance have been endless. When automation technologies started making headlines, everyone fixated on all the statistics around jobless due to automation. The Washington Post last year reported that robots would replace almost a third of the U.S. workforce by 2030. Many AI-powered technologies have garnered some bad press but IT teams are one of the first groups to experiment and more formally adopt AI technologies — not to replace humans but to complement our advancements

According to a recent study conducted by Tata Consultancy Services(TCS), 46% of the companies surveyed said their IT departments are using AI. But for what? Mostly for security intrusions, resolving user issues, automating production management and gauging internal compliance.


AI in The Real World

According to the TCS study, the highest percentage of organizations using AI is in the energy industry, with 100% of them using AI to some capacity, followed by high-tech and telecommunications.

But why are these IT teams and other departments investing in AI technologies? The study outlines six main goals that really propel AI initiatives:

■ Improving product or service quality

■ Helping customers use and get more value from their products/and or services

■ Reducing key process cycle times

■ Improving executive decisions

■ Identifying new revenue opportunities

■ Reducing costs by automating manual work

Ultimately, whether using AI for security intrusions, IT problems or otherwise, the main driver for IT in using this technology is to improve product and service quality. That is why it is no surprise that IT vendors have been developing AI solutions for IT professionals in the end-user computing space, be it for application, hardware, services management, etc.

Particularly, as it pertains to tools that monitor the digital experience, AI technologies help support this goal while also helping clear up IT's time for higher value activities.

How AI Will Transform IT Operations in 2019?

Gartner recently published its Top 10 Strategic Technology Trends for 2019 which outlines the empowered edge as a top trend noting: "Through 2028, we expect a steady increase in the embedding of sensor, storage, compute and advanced AI capabilities in edge devices."

With the introduction of AI into IT operations, IT teams continue to find new use cases for AI and its applicability to edge computing is no exception. Perhaps one of the most promising use cases in this space, in part because of its clear and strong business value proposition, is Level 0 support, an automated or self-service style where users can access help themselves without the aid of the help desk. AI technologies, used in tandem with end-user computing or digital experience monitoring tools, are now being used to deflect user-facing issues from even reaching support desks using self-healing and self-service — Level 0 support.

AI's role in Level 0 is identifying patterns in the monitored environment that can then help inform IT or automation technologies to solve a problem. The value proposition of such solutions is simple, it is a way to reduce support desk costs and free up agents' time to focus on higher value interactions, which are more complex issues and require humans.

Some components of Level 0 support are not new. Unfortunately, this level of support has not been executed successfully by many IT departments. With AI advancements, the future seems very promising for the effectiveness of self-service programs and the adoption of new automation processes that ultimately help improve quality for users.

Hot Topics

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Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

How IT Departments Are Successfully Adopting Artificial Intelligence Technologies

Patricia Diaz-Hymes

We all know artificial intelligence (AI) is a hot topic — but beyond the buzzword, have you ever wondered how IT departments are actually adopting AI technologies to improve on their operations?

Because the term "AI" gets thrown around a lot, let's start with what it means. Given all the marketing hype this technology has been given, I often find myself debating with peers on what AI actually is. Understanding that many vendors have usurped some loose sense of the term in order to claim AI functionality, let's be factual in terms of what it is. As Gartner defines it, artificial intelligence is:

"Technology that appears to emulate human performance typically by learning, coming to its own conclusions, appearing to understand complex content, engaging in natural dialogs with people, enhancing human cognitive performance (also known as cognitive computing) or replacing people on execution of nonroutine tasks. Applications include autonomous vehicles, automatic speech recognition and generation and detecting novel concepts and abstractions (useful for detecting potential new risks and aiding humans quickly understand very large bodies of ever-changing information)."

46% of the companies surveyed said their IT departments are using AI

Use cases for understanding AI as technology that emulates human performance have been endless. When automation technologies started making headlines, everyone fixated on all the statistics around jobless due to automation. The Washington Post last year reported that robots would replace almost a third of the U.S. workforce by 2030. Many AI-powered technologies have garnered some bad press but IT teams are one of the first groups to experiment and more formally adopt AI technologies — not to replace humans but to complement our advancements

According to a recent study conducted by Tata Consultancy Services(TCS), 46% of the companies surveyed said their IT departments are using AI. But for what? Mostly for security intrusions, resolving user issues, automating production management and gauging internal compliance.


AI in The Real World

According to the TCS study, the highest percentage of organizations using AI is in the energy industry, with 100% of them using AI to some capacity, followed by high-tech and telecommunications.

But why are these IT teams and other departments investing in AI technologies? The study outlines six main goals that really propel AI initiatives:

■ Improving product or service quality

■ Helping customers use and get more value from their products/and or services

■ Reducing key process cycle times

■ Improving executive decisions

■ Identifying new revenue opportunities

■ Reducing costs by automating manual work

Ultimately, whether using AI for security intrusions, IT problems or otherwise, the main driver for IT in using this technology is to improve product and service quality. That is why it is no surprise that IT vendors have been developing AI solutions for IT professionals in the end-user computing space, be it for application, hardware, services management, etc.

Particularly, as it pertains to tools that monitor the digital experience, AI technologies help support this goal while also helping clear up IT's time for higher value activities.

How AI Will Transform IT Operations in 2019?

Gartner recently published its Top 10 Strategic Technology Trends for 2019 which outlines the empowered edge as a top trend noting: "Through 2028, we expect a steady increase in the embedding of sensor, storage, compute and advanced AI capabilities in edge devices."

With the introduction of AI into IT operations, IT teams continue to find new use cases for AI and its applicability to edge computing is no exception. Perhaps one of the most promising use cases in this space, in part because of its clear and strong business value proposition, is Level 0 support, an automated or self-service style where users can access help themselves without the aid of the help desk. AI technologies, used in tandem with end-user computing or digital experience monitoring tools, are now being used to deflect user-facing issues from even reaching support desks using self-healing and self-service — Level 0 support.

AI's role in Level 0 is identifying patterns in the monitored environment that can then help inform IT or automation technologies to solve a problem. The value proposition of such solutions is simple, it is a way to reduce support desk costs and free up agents' time to focus on higher value interactions, which are more complex issues and require humans.

Some components of Level 0 support are not new. Unfortunately, this level of support has not been executed successfully by many IT departments. With AI advancements, the future seems very promising for the effectiveness of self-service programs and the adoption of new automation processes that ultimately help improve quality for users.

Hot Topics

The Latest

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...