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AIOps = Brains (AI) + Brawn (Automation)

Valerie O'Connell
EMA

Artificial intelligence (AI) may be the brains, but when the market hears the term "AIOps," it puts automation in the mix. After all, what is the use of knowing without doing?

Recent EMA research, AI(work)Ops 2021: The State of AIOps took a ground-level look at AIOps as it is used globally today and as planned in the coming months — a view more practical than aspirational. As it turns out, AI and automation form the one-two punch that makes digital service excellence possible in what is otherwise an impossible complexity of IT operations.

Both AIOps and automation are C-suite winners, strategic and enterprise-wide for organizations that self-rate their AIOps implementations as highly successful. However, automation holds the edge. When EMA explicitly separated AIOps and automation, more than half of all research participants identified automation as a C-suite initiative, strategic across the enterprise, while AIOps weighed in at 32%. An interesting side note is that, when it comes to automation, CFOs join CIOs in having a significant decision-making role, presumably because there is a fairly straight line between automation and savings.

The Double-Edged Sword

Yet, automation is a double-edged sword. Beloved by CXOs both in theory and in budget allocations, it is a harder sell on the ground, especially when it is paired with AI and machine learning (ML). In addition to the time-honored resistance to change that accompanies almost all major IT initiatives, AIOps automation faces deep-rooted fear and distrust.

EMA research shows that AI-driven automation is an acquired taste. As organizations gain experience, that experience is statistically highly likely to be positive, productive, and profitable. Just as success breeds success, automation breeds automation. It follows that the more mature AIOps implementations are also the most advanced in terms of number, types, and degree of automation in play.

What was a little bit more surprising was that all-autonomous automation is not the universal endgame. The preferred state is increased automation that retains a human touch.


The Pain/Gain Ratio

Asked, "How would you characterize the value AIOps brings to your organization relative to the cost?" respondents were almost unanimous in achieving value. The difference was in degree. Offered a range of answers, including negative ones that no one selected, 17% rated AIOps value as a break even proposition, 41% chose "high" value, and 21% cited "very high" value relative to cost. EMA went on to explore the detail and range of benefits that comprise this value, both qualitative and quantitative. For instance, asked about the impact of AIOps on the relationship between IT and the rest of the business, 99% of the responses were positive. Notably, 21% chose the superlative "transformational" to describe that impact.

Although the gains are plentiful, the path to AIOps benefits is neither fast nor easy. Asked to rate the rigor of AIOps implementation, only 18% characterized the process as either "smooth" or "relatively easy." The rest ranged between "straightforward, but not easy" (28%) and "very difficult" (11%), with 43% choosing the midpoint "challenging" as the best descriptor. Asked to enumerate those challenges, respondents ranked cost, data, and conflicts within IT as the top impediments to AIOps initiatives.

Addressing the Data Dilemma

EMA research and experience show that cost holds a leading position in the list of challenges for all major IT initiatives, as does conflict within IT. However, the challenge of data accuracy and accessibility holds an elevated role in AIOps because of the wide range of data sources involved in its implementation and its high reliance on data in execution. For that reason, smoothing data issues can accelerate AIOps initiatives and the benefits that will predictably attend success.

Valerie O'Connell is EMA Research Director of Digital Service Execution

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AIOps = Brains (AI) + Brawn (Automation)

Valerie O'Connell
EMA

Artificial intelligence (AI) may be the brains, but when the market hears the term "AIOps," it puts automation in the mix. After all, what is the use of knowing without doing?

Recent EMA research, AI(work)Ops 2021: The State of AIOps took a ground-level look at AIOps as it is used globally today and as planned in the coming months — a view more practical than aspirational. As it turns out, AI and automation form the one-two punch that makes digital service excellence possible in what is otherwise an impossible complexity of IT operations.

Both AIOps and automation are C-suite winners, strategic and enterprise-wide for organizations that self-rate their AIOps implementations as highly successful. However, automation holds the edge. When EMA explicitly separated AIOps and automation, more than half of all research participants identified automation as a C-suite initiative, strategic across the enterprise, while AIOps weighed in at 32%. An interesting side note is that, when it comes to automation, CFOs join CIOs in having a significant decision-making role, presumably because there is a fairly straight line between automation and savings.

The Double-Edged Sword

Yet, automation is a double-edged sword. Beloved by CXOs both in theory and in budget allocations, it is a harder sell on the ground, especially when it is paired with AI and machine learning (ML). In addition to the time-honored resistance to change that accompanies almost all major IT initiatives, AIOps automation faces deep-rooted fear and distrust.

EMA research shows that AI-driven automation is an acquired taste. As organizations gain experience, that experience is statistically highly likely to be positive, productive, and profitable. Just as success breeds success, automation breeds automation. It follows that the more mature AIOps implementations are also the most advanced in terms of number, types, and degree of automation in play.

What was a little bit more surprising was that all-autonomous automation is not the universal endgame. The preferred state is increased automation that retains a human touch.


The Pain/Gain Ratio

Asked, "How would you characterize the value AIOps brings to your organization relative to the cost?" respondents were almost unanimous in achieving value. The difference was in degree. Offered a range of answers, including negative ones that no one selected, 17% rated AIOps value as a break even proposition, 41% chose "high" value, and 21% cited "very high" value relative to cost. EMA went on to explore the detail and range of benefits that comprise this value, both qualitative and quantitative. For instance, asked about the impact of AIOps on the relationship between IT and the rest of the business, 99% of the responses were positive. Notably, 21% chose the superlative "transformational" to describe that impact.

Although the gains are plentiful, the path to AIOps benefits is neither fast nor easy. Asked to rate the rigor of AIOps implementation, only 18% characterized the process as either "smooth" or "relatively easy." The rest ranged between "straightforward, but not easy" (28%) and "very difficult" (11%), with 43% choosing the midpoint "challenging" as the best descriptor. Asked to enumerate those challenges, respondents ranked cost, data, and conflicts within IT as the top impediments to AIOps initiatives.

Addressing the Data Dilemma

EMA research and experience show that cost holds a leading position in the list of challenges for all major IT initiatives, as does conflict within IT. However, the challenge of data accuracy and accessibility holds an elevated role in AIOps because of the wide range of data sources involved in its implementation and its high reliance on data in execution. For that reason, smoothing data issues can accelerate AIOps initiatives and the benefits that will predictably attend success.

Valerie O'Connell is EMA Research Director of Digital Service Execution

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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