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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.

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Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

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

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...