Skip to main content

What Can AIOps Do For IT Ops? - Part 3

APMdigest asked the top minds in the industry what they think AIOps can do for IT Operations. Part 3 covers abilities AIOps gives to IT Operations, such as speed and efficiency.

Start with What Can AIOps Do For IT Ops? - Part 1

Start with What Can AIOps Do For IT Ops? - Part 2

PROACTIVE RESPONSIVENESS

Embracing Observability with AIOps gives time back to developers and SREs; it makes their lives easier, so they can focus on improvements and innovation. AIOps surfaces real insights and automates workflows to indicate when there's issues forming — sometimes before they result in an outage — guiding users to the probable root cause of the issue, thus allowing users and teams to fix issues faster and take a proactive approach to prevent future issues from happening. AIOps eliminates the need to manually verify builds, tests, deploys, and releases, and also the need to switch between dashboards communications channels. The collaboration aspects built directly into, and integrated with, a solution unite users with the data and information they need to make informed and proactive decisions.
Adam Frank
VP, Product Management & UX Design, Moogsoft

REAL-TIME RESPONSIVENESS

Under the umbrella of AIOps solutions are features that help teams respond and resolve issues more quickly and as efficiently as possible. Real-time response is a priority for any organization serving customers with high expectations for their digital experience. The pressure on digital service providers continues to increase at an unprecedented pace. In fact, according to Gartner, the average cost to companies of IT downtime is almost $6,000 per minute and can range anywhere from $140,000 per hour to as much as $540,000 per hour. Almost one-third of enterprise companies reported one hour of downtime could cost their business $1-5 million.
Andrew Marshall
Sr. Director of Product Marketing and Advocacy, PagerDuty

SPEED AND EFFICIENCY

AIOps exists to make IT operations efficient and fast by taking advantage of machine learning and big data. With the proper usage, AIOps helps teams act with speed and efficiency and respond to issues proactively and in real-time. This has proven to be a necessity in our new world of working, as organizations need to remain agile and resilient in the face of the next business disruption. This is a game-changer for IT, as teams would be left to solve issues manually, and now, AIOps frees them up to focus on more important tasks.
Gab Menachem
Senior Director, Product Management, ITOM, ServiceNow, and founder and CEO of Loom Systems (a ServiceNow company)

REDUCED MTTR

AIOps helps Dev and Ops teams deliver improvement across the primary SLOs for application reliability and resiliency: MTTR (mean time to resolution) of issues, less system downtime and more time between failures, and faster application response time because of better maintenance.
Jason English
Principal Analyst, Intellyx

IT Central Station users have been impressed with the way AIOps help reduce their mean time to repair (MTTR). This is an important factor for companies that are reliant on their critical IT applications.
Russell Rothstein
Founder and CEO, IT Central Station

Using analytics linked to automation AIOps enables IT operations teams to identify, address and resolve issues more effectively than traditional manual-powered functions. AIOps puts the technology and tools needed to support operational efficiency in one central location — resulting in a more automated and collaborative network that significantly reduces resolution time.
Michael Procopio
Product Marketing Manager, Micro Focus

Today, most enterprises struggle when it comes to technology operations and processes around operations like ITIL. AIOps is going to be the next-gen Ops word for the next 2-3 years around predictive intelligence and predictive insights using artificial intelligence. AIOps will help teams prevent issues occurring in the first place using pattern analysis and also do proactive monitoring. Converting the knowledge base on the repeated issues into knowledge scripts will help reduce the MTTR by invoking those scripts based on the knowledge-based scripts during the failure.
Vishnu Vasudevan
Head of Product Engineering and Management, Opsera

MANAGING NETWORK PERFORMANCE

EMA research has found that 90% of IT organizations believe that applying AIOps to network infrastructure and operations can lead to better overall business outcomes for a company. They find it particularly useful for optimizing their network infrastructure, driving operational efficiency, and reducing security and compliance risk. It isn't easy to achieve these benefits. Only 28% of the IT organizations that are active with applying AIOps to network management consider themselves fully successful with these technology engagements. One big pitfall is risk. While they think AIOps can reduce security and compliance risk, they also think that it might introduce more risk if implemented poorly. They're also struggling with network complexity and data quality. Bad data leads to bad AIOps outcomes.
Shamus McGillicuddy
VP of Research, Networking, Enterprise Management Associates (EMA)

View an on-demand webinar with EMA's Shamus McGillicuddy: Revolutionizing Network Management with AIOps

As networks become more complex and workloads become more distributed, AIOps and virtual AI assistants are increasing becoming essential members of future IT teams. These virtual AI assistants with conversational interfaces are more efficient at viewing the network and managing the end-to-end user experience. As enterprises increasingly move to cloud-managed solutions and services, network vendors whose organizations integrate their customer support, and DevOps teams, with their AIOps data science teams, are fundamentally changing the customer support experience. Enterprises are finding fewer support issues and better visibility as network data moves to the cloud, as well as proactive support such as automated RMA, where their vendor knows a network element needs to be replaced before they do.
Bob Friday
VP and AI Chief Scientist, Juniper Networks

When you think about what AIOps can do for IT Operations it's easy to say that it can do all things and be all things, but the truth behind AIOps is that it will be as good as the data it's fed, and the outcomes you expect. And as we make advancements in AI, ML, and approaches to advanced analytics, the right implementation of AIOps coupled with a complete data set will empower IT organizations to be nimble, accurate, and calculated in their decisions when facing performance issues with critical business applications. While it doesn't replace the operator, it enabled the operator to be pin-point accurate reducing the MTTR and maintaining the high levels of network performance users expect.
Brandon Carroll
Director, Technical Evangelist, Riverbed

MANAGING PERFORMANCE IN THE CLOUD

Enterprises across industries are adopting cloud native patterns to rapidly build contactless, immersive experiences for their customers. But this increased velocity comes with increased complexity. As organizations adopt more cloud native patterns AIOps is a must have and not nice to have. Because without AI OPS there is no way enterprises can effectively manage infrastructure performance in a multi cloud environment or accurately predict capacity.
Milan Bhatt
EVP, Hexaware

Go to What Can AIOps Do For IT Ops? - Part 4

Hot Topics

The Latest

UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

AI can't fix broken data. CIOs who modernize revenue data governance unlock predictable growth-those who don't risk millions in failed AI investments. For decades, CIOs kept the lights on. Revenue was someone else's problem, owned by sales, led by the CRO, measured by finance. Those days are behind us ...

Over the past few years, organizations have made enormous strides in enabling remote and hybrid work. But the foundational technologies powering today's digital workplace were never designed for the volume, velocity, and complexity that is coming next. By 2026 and beyond, three forces — 5G, the metaverse, and edge AI — will fundamentally reshape how people connect, collaborate, and access enterprise resources ... The businesses that begin preparing now will gain a competitive head start. Those that wait will find themselves trying to secure environments that have already outgrown their architecture ...

Ask where enterprise AI is making its most decisive impact, and the answer might surprise you: not marketing, not finance, not customer experience. It's IT. Across three years of industry research conducted by Digitate, one constant holds true is that IT is both the testing ground and the proving ground for enterprise AI. Last year, that position only strengthened ...

A payment gateway fails at 2 AM. Thousands of transactions hang in limbo. Post-mortems reveal failures cascading across dozens of services, each technically sound in isolation. The diagnosis takes hours. The fix requires coordinated deployments across teams ...

Every enterprise technology conversation right now circles back to AI agents. And for once, the excitement isn't running too far ahead of reality. According to a Zapier survey of over 500 enterprise leaders, 72% of enterprises are already using or testing AI agents, and 84% plan to increase their investment over the next 12 months. Those numbers are big. But they also raise a question that doesn't get asked enough: what exactly are companies doing with these agents, and are they actually getting value from them? ...

Many organizations still rely on reactive availability models, taking action only after an outage occurs. However, as applications become more complex, this approach often leads to delayed detection, prolonged disruption, and incomplete recovery. Monitoring is evolving from a basic operational function into a foundational capability for sustaining availability in modern environments ...

In MEAN TIME TO INSIGHT Episode 22, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses DNS Security ... 

The financial stakes of extended service disruption has made operational resilience a top priority, according to 2026 State of AI-First Operations Report, a report from PagerDuty. According to survey findings, 95% of respondents believe their leadership understands the competitive advantage that can be gained from reducing incidents and speeding recovery ...

What Can AIOps Do For IT Ops? - Part 3

APMdigest asked the top minds in the industry what they think AIOps can do for IT Operations. Part 3 covers abilities AIOps gives to IT Operations, such as speed and efficiency.

Start with What Can AIOps Do For IT Ops? - Part 1

Start with What Can AIOps Do For IT Ops? - Part 2

PROACTIVE RESPONSIVENESS

Embracing Observability with AIOps gives time back to developers and SREs; it makes their lives easier, so they can focus on improvements and innovation. AIOps surfaces real insights and automates workflows to indicate when there's issues forming — sometimes before they result in an outage — guiding users to the probable root cause of the issue, thus allowing users and teams to fix issues faster and take a proactive approach to prevent future issues from happening. AIOps eliminates the need to manually verify builds, tests, deploys, and releases, and also the need to switch between dashboards communications channels. The collaboration aspects built directly into, and integrated with, a solution unite users with the data and information they need to make informed and proactive decisions.
Adam Frank
VP, Product Management & UX Design, Moogsoft

REAL-TIME RESPONSIVENESS

Under the umbrella of AIOps solutions are features that help teams respond and resolve issues more quickly and as efficiently as possible. Real-time response is a priority for any organization serving customers with high expectations for their digital experience. The pressure on digital service providers continues to increase at an unprecedented pace. In fact, according to Gartner, the average cost to companies of IT downtime is almost $6,000 per minute and can range anywhere from $140,000 per hour to as much as $540,000 per hour. Almost one-third of enterprise companies reported one hour of downtime could cost their business $1-5 million.
Andrew Marshall
Sr. Director of Product Marketing and Advocacy, PagerDuty

SPEED AND EFFICIENCY

AIOps exists to make IT operations efficient and fast by taking advantage of machine learning and big data. With the proper usage, AIOps helps teams act with speed and efficiency and respond to issues proactively and in real-time. This has proven to be a necessity in our new world of working, as organizations need to remain agile and resilient in the face of the next business disruption. This is a game-changer for IT, as teams would be left to solve issues manually, and now, AIOps frees them up to focus on more important tasks.
Gab Menachem
Senior Director, Product Management, ITOM, ServiceNow, and founder and CEO of Loom Systems (a ServiceNow company)

REDUCED MTTR

AIOps helps Dev and Ops teams deliver improvement across the primary SLOs for application reliability and resiliency: MTTR (mean time to resolution) of issues, less system downtime and more time between failures, and faster application response time because of better maintenance.
Jason English
Principal Analyst, Intellyx

IT Central Station users have been impressed with the way AIOps help reduce their mean time to repair (MTTR). This is an important factor for companies that are reliant on their critical IT applications.
Russell Rothstein
Founder and CEO, IT Central Station

Using analytics linked to automation AIOps enables IT operations teams to identify, address and resolve issues more effectively than traditional manual-powered functions. AIOps puts the technology and tools needed to support operational efficiency in one central location — resulting in a more automated and collaborative network that significantly reduces resolution time.
Michael Procopio
Product Marketing Manager, Micro Focus

Today, most enterprises struggle when it comes to technology operations and processes around operations like ITIL. AIOps is going to be the next-gen Ops word for the next 2-3 years around predictive intelligence and predictive insights using artificial intelligence. AIOps will help teams prevent issues occurring in the first place using pattern analysis and also do proactive monitoring. Converting the knowledge base on the repeated issues into knowledge scripts will help reduce the MTTR by invoking those scripts based on the knowledge-based scripts during the failure.
Vishnu Vasudevan
Head of Product Engineering and Management, Opsera

MANAGING NETWORK PERFORMANCE

EMA research has found that 90% of IT organizations believe that applying AIOps to network infrastructure and operations can lead to better overall business outcomes for a company. They find it particularly useful for optimizing their network infrastructure, driving operational efficiency, and reducing security and compliance risk. It isn't easy to achieve these benefits. Only 28% of the IT organizations that are active with applying AIOps to network management consider themselves fully successful with these technology engagements. One big pitfall is risk. While they think AIOps can reduce security and compliance risk, they also think that it might introduce more risk if implemented poorly. They're also struggling with network complexity and data quality. Bad data leads to bad AIOps outcomes.
Shamus McGillicuddy
VP of Research, Networking, Enterprise Management Associates (EMA)

View an on-demand webinar with EMA's Shamus McGillicuddy: Revolutionizing Network Management with AIOps

As networks become more complex and workloads become more distributed, AIOps and virtual AI assistants are increasing becoming essential members of future IT teams. These virtual AI assistants with conversational interfaces are more efficient at viewing the network and managing the end-to-end user experience. As enterprises increasingly move to cloud-managed solutions and services, network vendors whose organizations integrate their customer support, and DevOps teams, with their AIOps data science teams, are fundamentally changing the customer support experience. Enterprises are finding fewer support issues and better visibility as network data moves to the cloud, as well as proactive support such as automated RMA, where their vendor knows a network element needs to be replaced before they do.
Bob Friday
VP and AI Chief Scientist, Juniper Networks

When you think about what AIOps can do for IT Operations it's easy to say that it can do all things and be all things, but the truth behind AIOps is that it will be as good as the data it's fed, and the outcomes you expect. And as we make advancements in AI, ML, and approaches to advanced analytics, the right implementation of AIOps coupled with a complete data set will empower IT organizations to be nimble, accurate, and calculated in their decisions when facing performance issues with critical business applications. While it doesn't replace the operator, it enabled the operator to be pin-point accurate reducing the MTTR and maintaining the high levels of network performance users expect.
Brandon Carroll
Director, Technical Evangelist, Riverbed

MANAGING PERFORMANCE IN THE CLOUD

Enterprises across industries are adopting cloud native patterns to rapidly build contactless, immersive experiences for their customers. But this increased velocity comes with increased complexity. As organizations adopt more cloud native patterns AIOps is a must have and not nice to have. Because without AI OPS there is no way enterprises can effectively manage infrastructure performance in a multi cloud environment or accurately predict capacity.
Milan Bhatt
EVP, Hexaware

Go to What Can AIOps Do For IT Ops? - Part 4

Hot Topics

The Latest

UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

AI can't fix broken data. CIOs who modernize revenue data governance unlock predictable growth-those who don't risk millions in failed AI investments. For decades, CIOs kept the lights on. Revenue was someone else's problem, owned by sales, led by the CRO, measured by finance. Those days are behind us ...

Over the past few years, organizations have made enormous strides in enabling remote and hybrid work. But the foundational technologies powering today's digital workplace were never designed for the volume, velocity, and complexity that is coming next. By 2026 and beyond, three forces — 5G, the metaverse, and edge AI — will fundamentally reshape how people connect, collaborate, and access enterprise resources ... The businesses that begin preparing now will gain a competitive head start. Those that wait will find themselves trying to secure environments that have already outgrown their architecture ...

Ask where enterprise AI is making its most decisive impact, and the answer might surprise you: not marketing, not finance, not customer experience. It's IT. Across three years of industry research conducted by Digitate, one constant holds true is that IT is both the testing ground and the proving ground for enterprise AI. Last year, that position only strengthened ...

A payment gateway fails at 2 AM. Thousands of transactions hang in limbo. Post-mortems reveal failures cascading across dozens of services, each technically sound in isolation. The diagnosis takes hours. The fix requires coordinated deployments across teams ...

Every enterprise technology conversation right now circles back to AI agents. And for once, the excitement isn't running too far ahead of reality. According to a Zapier survey of over 500 enterprise leaders, 72% of enterprises are already using or testing AI agents, and 84% plan to increase their investment over the next 12 months. Those numbers are big. But they also raise a question that doesn't get asked enough: what exactly are companies doing with these agents, and are they actually getting value from them? ...

Many organizations still rely on reactive availability models, taking action only after an outage occurs. However, as applications become more complex, this approach often leads to delayed detection, prolonged disruption, and incomplete recovery. Monitoring is evolving from a basic operational function into a foundational capability for sustaining availability in modern environments ...

In MEAN TIME TO INSIGHT Episode 22, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses DNS Security ... 

The financial stakes of extended service disruption has made operational resilience a top priority, according to 2026 State of AI-First Operations Report, a report from PagerDuty. According to survey findings, 95% of respondents believe their leadership understands the competitive advantage that can be gained from reducing incidents and speeding recovery ...