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Automation Will Propel the Future of IT

Phil Tee

The IT industry has been changing shape and scope for decades. Over the course of my career, I've witnessed first hand how innovative technologies have assisted IT professionals to overcome their most daunting challenges.

Currently, we're seeing artificial intelligence for IT operations or "AIOps" take center stage in the IT industry. If AIOps hasn't been on your horizon yet, look closely and expect it soon. The leading analyst firm Gartner has predictedthat "by 2020, approximately 50 percent of enterprises will actively use AIOps technologies together with APM to provide insight into both business execution and IT operations, up from fewer than 10 percent today."

So what can we expect from automation and AIOps as it becomes more commonplace? Let's dive in.

Automation Boosts IT Productivity

If technology is handling tasks previously owned and managed by a human, will it eliminate their role?

Automation is no enemy to IT teams

No, with man and machine together, businesses can thrive and employees can feel like their jobs are safe. I understand that change can be difficult, but automation is no enemy to IT teams. PwC found that 73 percent of workers believe that technology can never replace the human mind. It's clear that human beings — not automation — will continue to be the driving force behind IT.

The common IT experience is reactive, rather than proactive work. This forces teams to slog through endless monitoring of various dashboards or countless service tickets. When we apply automation technologies, a new type of proactive work is possible: one where professionals have dedicated time to improve products, platforms, and services.

Alongside this productivity boost, employees may also see more opportunity to finally wrap up work on time. IT professionals can take the much-needed disconnection from devices, and instead focus their time out of work on their family, hobbies or passions. Late nights in the office can become a thing of the past, as AI manages monitoring and other menial tasks.

With Automation, IT Receives Some Much-Needed Recognition

In Moogsoft's Heard from the Herd podcast, Jill Lehman, Vice President of Corporate Services & Chief People Officer at Ontario Systems, and Andy Brown, CEO and Founder of Sand Hill East (and a Moogsoft board member), shared their perspective on automation working alongside IT teams.

From Jill's perspective, "Learning agility is what happens when you accept automation or the different technologies that help you do work, which means that once a task is automated, people have the opportunity to pivot to a new type of thinking or work that expands upon and innovates from their foundational knowledge."

Andy shared this bit of wisdom: "There are definitely common traits that I find in the most successful people. For example, you may have heard the phrase ‘listening is at the heart of being innovative,' but to that, I would also add: if you know everything, you can't learn anything. I truly believe that listening is important and a skill to develop. Listen to the client, investors, and advisors. Take what you hear and learn to apply it."

This insight shows a significant difference between humans and machines: humans have the ability to listen, think critically, and apply their learnings at a much faster and more knowledgeable level, while machines do exactly as they're told. The most advanced machine-learning algorithms cannot surpass the human mind, especially when it comes to quick, reactive decision making.

IT Has All The Power and Potential to Grow

The future is automated, and my hope is that we can be excited about this shift. Change is important, but Gartner paints a bright outlook: emergent technology like AI will create 2.3 million jobs by 2020.

We're at the dawn of something big, akin to the excitement buzzing around the Industrial Revolution. We're taking great strides toward a new type of life: one where we can all live and work comfortably and enthusiastically alongside machines.

The Latest

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 4 covers negative impacts of AI ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 3 covers barriers and challenges for AI ...

Automation Will Propel the Future of IT

Phil Tee

The IT industry has been changing shape and scope for decades. Over the course of my career, I've witnessed first hand how innovative technologies have assisted IT professionals to overcome their most daunting challenges.

Currently, we're seeing artificial intelligence for IT operations or "AIOps" take center stage in the IT industry. If AIOps hasn't been on your horizon yet, look closely and expect it soon. The leading analyst firm Gartner has predictedthat "by 2020, approximately 50 percent of enterprises will actively use AIOps technologies together with APM to provide insight into both business execution and IT operations, up from fewer than 10 percent today."

So what can we expect from automation and AIOps as it becomes more commonplace? Let's dive in.

Automation Boosts IT Productivity

If technology is handling tasks previously owned and managed by a human, will it eliminate their role?

Automation is no enemy to IT teams

No, with man and machine together, businesses can thrive and employees can feel like their jobs are safe. I understand that change can be difficult, but automation is no enemy to IT teams. PwC found that 73 percent of workers believe that technology can never replace the human mind. It's clear that human beings — not automation — will continue to be the driving force behind IT.

The common IT experience is reactive, rather than proactive work. This forces teams to slog through endless monitoring of various dashboards or countless service tickets. When we apply automation technologies, a new type of proactive work is possible: one where professionals have dedicated time to improve products, platforms, and services.

Alongside this productivity boost, employees may also see more opportunity to finally wrap up work on time. IT professionals can take the much-needed disconnection from devices, and instead focus their time out of work on their family, hobbies or passions. Late nights in the office can become a thing of the past, as AI manages monitoring and other menial tasks.

With Automation, IT Receives Some Much-Needed Recognition

In Moogsoft's Heard from the Herd podcast, Jill Lehman, Vice President of Corporate Services & Chief People Officer at Ontario Systems, and Andy Brown, CEO and Founder of Sand Hill East (and a Moogsoft board member), shared their perspective on automation working alongside IT teams.

From Jill's perspective, "Learning agility is what happens when you accept automation or the different technologies that help you do work, which means that once a task is automated, people have the opportunity to pivot to a new type of thinking or work that expands upon and innovates from their foundational knowledge."

Andy shared this bit of wisdom: "There are definitely common traits that I find in the most successful people. For example, you may have heard the phrase ‘listening is at the heart of being innovative,' but to that, I would also add: if you know everything, you can't learn anything. I truly believe that listening is important and a skill to develop. Listen to the client, investors, and advisors. Take what you hear and learn to apply it."

This insight shows a significant difference between humans and machines: humans have the ability to listen, think critically, and apply their learnings at a much faster and more knowledgeable level, while machines do exactly as they're told. The most advanced machine-learning algorithms cannot surpass the human mind, especially when it comes to quick, reactive decision making.

IT Has All The Power and Potential to Grow

The future is automated, and my hope is that we can be excited about this shift. Change is important, but Gartner paints a bright outlook: emergent technology like AI will create 2.3 million jobs by 2020.

We're at the dawn of something big, akin to the excitement buzzing around the Industrial Revolution. We're taking great strides toward a new type of life: one where we can all live and work comfortably and enthusiastically alongside machines.

The Latest

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 4 covers negative impacts of AI ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 3 covers barriers and challenges for AI ...