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Built-in Monitoring Is Most Important AIOps Feature

Built-in monitoring/native instrumentation ranked as the most important feature of an AIOps solution, cited by nearly 55% of respondents in a new study from OpsRamp, The State of AIOps 2023.

The study concludes that AIOps is delivering real benefits for enterprises and MSPs, even as two-thirds of respondents have concerns about how accurate the data going into their AIOps systems is.

With the global economy facing headwinds on multiple fronts including inflation, the cost-of-living crisis, higher interest rates and war in Ukraine, both enterprises and MSPs are focused on improving IT efficiency and automation in 2023. MSPs cited improving operational efficiencies as their No. 1 challenge to achieving steady growth and profitability, while enterprises pointed to automating as many operations as possible as the biggest need or challenge they were trying to overcome in 2023.

While more than 60% of respondents were adopting AIOps to improve service and application availability and performance, the second and third top choices were for automation of operations (58%) and processes (54%).

Meanwhile, the greatest IT operations challenge for enterprises in 2023 was automating as many operations as possible, cited by 66% of respondents. Yet barely half of respondents (52%) cited automation of tedious tasks as their primary operational benefit of AIOps, trailing reduction in open incident tickets (65%) and reduction in MTTD and MTTR (56%). Improvements in automation are clearly top of mind for enterprises and MSPs in 2023.

Other key findings include:

■ Application to infrastructure dependency mapping is the top incident management challenge for enterprises and MSPs, cited by 64% of total respondents.

■ Intelligent alerting is the No. 1 use case for AIOps today for both enterprises (70%) and MSPs (66%).

■ The vast majority of AIOps implementations—more than 80%—take six months or less.

■ Data accuracy was respondents' biggest concern about AIOps, cited by 70% of MSPs and 62% of enterprises.

■ AIOps is creating jobs, not killing them, though engineers with the right skillsets for AIOps remain hard to find. Just 36% of respondents were concerned about AIOps deployment causing job loss while 68% said it takes more than six months to hire engineers with the right skillsets for AIOps

"The study shows that AIOps is real and is delivering tangible benefits for enterprises and MSPs," said Suresh Vobbilesetty, EVP, Engineering at OpsRamp. "But it also shows that organizations' AIOps initiatives remain a work in progress and have a ways to go before they can realize the full potential of the technology."

Methodology: The study was conducted in December by a third party research firm, and includes input from 265 respondents who work at the general manager, director or vice president level at enterprises and MSPs in North America, Europe or Asia Pacific. All respondents have budget decision-making responsibilities for IT monitoring tools, and work at firms with at least $25 million in annual revenue and more than 500 employees.

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Built-in Monitoring Is Most Important AIOps Feature

Built-in monitoring/native instrumentation ranked as the most important feature of an AIOps solution, cited by nearly 55% of respondents in a new study from OpsRamp, The State of AIOps 2023.

The study concludes that AIOps is delivering real benefits for enterprises and MSPs, even as two-thirds of respondents have concerns about how accurate the data going into their AIOps systems is.

With the global economy facing headwinds on multiple fronts including inflation, the cost-of-living crisis, higher interest rates and war in Ukraine, both enterprises and MSPs are focused on improving IT efficiency and automation in 2023. MSPs cited improving operational efficiencies as their No. 1 challenge to achieving steady growth and profitability, while enterprises pointed to automating as many operations as possible as the biggest need or challenge they were trying to overcome in 2023.

While more than 60% of respondents were adopting AIOps to improve service and application availability and performance, the second and third top choices were for automation of operations (58%) and processes (54%).

Meanwhile, the greatest IT operations challenge for enterprises in 2023 was automating as many operations as possible, cited by 66% of respondents. Yet barely half of respondents (52%) cited automation of tedious tasks as their primary operational benefit of AIOps, trailing reduction in open incident tickets (65%) and reduction in MTTD and MTTR (56%). Improvements in automation are clearly top of mind for enterprises and MSPs in 2023.

Other key findings include:

■ Application to infrastructure dependency mapping is the top incident management challenge for enterprises and MSPs, cited by 64% of total respondents.

■ Intelligent alerting is the No. 1 use case for AIOps today for both enterprises (70%) and MSPs (66%).

■ The vast majority of AIOps implementations—more than 80%—take six months or less.

■ Data accuracy was respondents' biggest concern about AIOps, cited by 70% of MSPs and 62% of enterprises.

■ AIOps is creating jobs, not killing them, though engineers with the right skillsets for AIOps remain hard to find. Just 36% of respondents were concerned about AIOps deployment causing job loss while 68% said it takes more than six months to hire engineers with the right skillsets for AIOps

"The study shows that AIOps is real and is delivering tangible benefits for enterprises and MSPs," said Suresh Vobbilesetty, EVP, Engineering at OpsRamp. "But it also shows that organizations' AIOps initiatives remain a work in progress and have a ways to go before they can realize the full potential of the technology."

Methodology: The study was conducted in December by a third party research firm, and includes input from 265 respondents who work at the general manager, director or vice president level at enterprises and MSPs in North America, Europe or Asia Pacific. All respondents have budget decision-making responsibilities for IT monitoring tools, and work at firms with at least $25 million in annual revenue and more than 500 employees.

Hot Topics

The Latest

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ...