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Discovering AIOps - Part 8: The Future of AIOps

Pete Goldin
APMdigest

The future of AIOps holds significant promise and potential, Ali Siddiqui, Chief Product Officer at BMC predicts. As technology continues to advance, AIOps is likely to play a crucial role in reshaping the landscape of IT operations and business processes. In the era of data-driven decision-making and automation, there will be a significant surge in the demand for AIOps and generative AI. The organizations that can effectively leverage the potential of these will be the ones defining the future landscape of enterprise software.

Overall, AIOps is poised to revolutionize how businesses manage their IT operations, making them more efficient, resilient, and customer-centric, Siddiqui continues. As the technology matures and becomes more widely adopted, it will undoubtedly bring about transformative changes across industries, contributing to improved business outcomes and customer satisfaction.

Start with: Discovering AIOps - Part 1

Start with: Discovering AIOps - Part 2: Must-Have Capabilities

Start with: Discovering AIOps - Part 3: The Users

Start with: Discovering AIOps - Part 4: Advantages

Start with: Discovering AIOps - Part 5: More Advantages

Start with: Discovering AIOps - Part 6: Challenges

Start with: Discovering AIOps - Part 7: The Current State of AIOps

Part 7 of this blog series covered the current state of AIOps. Now, in Part 8, the experts provide their visions for the future of AIOps:

Becoming the Norm

"I think AIOps becomes the norm and not hyped as the latest thing. I'm hopeful that more people quickly see the value and purpose faster so as to enable the adoption of more advanced automation," Carlos Casanova, Principal Analyst at Forrester Research

Helping but Not Replacing ITOPS

"AIOps has definitely changed the way we think about solving problems. In the least, it has allowed us to dream about what may be possible for this still nascent set of capabilities. Because that's what AIOps truly is — a set of capabilities. In the same way monitoring has evolved into a conversation about observability, automation and data (of all types) have evolved into a conversation about AIOps. And since capabilities are the true gateway to positive business outcomes, it is great to see that — according to the most recent SRE survey — reliability practitioners believe AIOPs will make their work easier (52%), while not replacing them (4%)," says Leo Vasiliou, Director of Product Marketing at Catchpoint.

Image removed.

"I believe that most of this technology will be in the form of a very intelligent assistant, rather than replace humans in the loop. I do think it will help eliminate a lot of the groundwork and help teams be more effective and faster in remediating problems," adds Spiros Xanthos, SVP and General Manager of Observability at Splunk.

Complementing Observability

"Observability plays a vital role, working hand-in-hand with AIOps to form a powerful combination, which complements and reinforces each other. An organization equipped with both can leverage AIOps for more intelligent and dynamic monitoring, featuring anomaly detection and advanced root cause analysis," says Siddiqui from BMC.

AIOps for Each Vertical

"People tend to only think about it in the context of alerting or applying CI/CD techniques to IT, but you can also see AIOps techniques applied across various industries and use cases. Health organizations used AIOps to report on COVID data that they collected from a variety of databases in different formats, for example. There are many more opportunities to apply AIOps to core business functions, and eventually engineering functions, too," says Camden Swita, Senior Product Manager at New Relic.

"There will be AIOps technology tailored for every vertical — retail, manufacturing, financial services, utilities, etc. These systems will train on machine data unique to each sector, so they'll offer more specific intelligence and insights," Monika Bhave, Product Manager at Digitate, predicts.

Generative AI Improves AIOps

"Generative AI will make AIOps better as complex orchestrations, automations, etc. will leverage natural language processing or other methods to better interact with what can be complex tooling," says Heath Newburn, Distinguished Field Engineer at PagerDuty.

Natural Language Interfaces

Carlos Casanova from Forrester says, "I see AIOps solutions having much more sophisticated Natural Language Interfaces (NLI) such that lower skilled/trained individuals can perform higher level work. This will hopefully offset some of the displacement that the automation is bringing."

"The next generation of AIOps platforms will offer some form of natural language processing interactions as a way to quickly ramp up a knowledge base that is easily understood by users," Thomas LaRock, Principal Developer Evangelist at Selector, agrees. "This is in contrast to legacy systems which rely on manual help files compiled by subject matter experts and need constant revisions. As AIOps continues to mature and become easier to implement as well as utilize, it will spread to every corner of the office in much the same way the Internet did 30 years ago — gradually, then suddenly."

Variety of Personas

"I see a scenario where the vendor's technologies are able to engage a variety of personas from service delivery, to engineering, to security to business owner," Carlos Casanova from Forrester envisions. "If the data is all the same from across the enterprise, there's no reason why there should be a multitude of tools segmented by persona. I speak to the current state of this from just the technology side in my Three Stages of Preparation For AIOps report. Picking your perspective is the first step."

Read the Forrester blog: Perspective Is Key To Understanding AIOps

Delivering on the Promise

"I think the future of AIOps is people actually doing AIOps. The AIOps space is at the peak of inflated expectations on the hype curve. I don't think people have realized value from AIOps in a meaningful way yet, so the future is about actually applying it. The future of AIOps is about delivering on its own productivity promise," says Bill Lobig, VP Product Management of Automation at IBM.

"AIOps gives the enterprise greater command over its monitored environment so the enterprise can adapt faster and with greater confidence. As enterprises adopt new technologies, rely increasingly on complex digital services to deliver value to customers and seek to connect IT organizations with business outcomes, AIOPs will be an important catalyst for change," Andreas Reiss, Head of Product Management, AIOps and Observability, at Broadcom, concludes. "Where that will lead is tremendously exciting."

Auto-Remediation

Probably the most important ultimate vision, and hope, for AIOps is auto-remediation.

“The movement toward higher levels of automation including automated remediation is accelerating. Typically this can be done on two levels — automated remediation requiring initial IT approval, and automated remediation that occurs on its own, but which should also document its actions in some way. There is definitely a move toward the latter, as both business and technology dynamics are becoming more accelerated,” says Dennis Drogseth, VP at Enterprise Management Associates (EMA).

Go to: Discovering AIOps - Part 9: Auto-Remediation

Pete Goldin is Editor and Publisher of APMdigest

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Discovering AIOps - Part 8: The Future of AIOps

Pete Goldin
APMdigest

The future of AIOps holds significant promise and potential, Ali Siddiqui, Chief Product Officer at BMC predicts. As technology continues to advance, AIOps is likely to play a crucial role in reshaping the landscape of IT operations and business processes. In the era of data-driven decision-making and automation, there will be a significant surge in the demand for AIOps and generative AI. The organizations that can effectively leverage the potential of these will be the ones defining the future landscape of enterprise software.

Overall, AIOps is poised to revolutionize how businesses manage their IT operations, making them more efficient, resilient, and customer-centric, Siddiqui continues. As the technology matures and becomes more widely adopted, it will undoubtedly bring about transformative changes across industries, contributing to improved business outcomes and customer satisfaction.

Start with: Discovering AIOps - Part 1

Start with: Discovering AIOps - Part 2: Must-Have Capabilities

Start with: Discovering AIOps - Part 3: The Users

Start with: Discovering AIOps - Part 4: Advantages

Start with: Discovering AIOps - Part 5: More Advantages

Start with: Discovering AIOps - Part 6: Challenges

Start with: Discovering AIOps - Part 7: The Current State of AIOps

Part 7 of this blog series covered the current state of AIOps. Now, in Part 8, the experts provide their visions for the future of AIOps:

Becoming the Norm

"I think AIOps becomes the norm and not hyped as the latest thing. I'm hopeful that more people quickly see the value and purpose faster so as to enable the adoption of more advanced automation," Carlos Casanova, Principal Analyst at Forrester Research

Helping but Not Replacing ITOPS

"AIOps has definitely changed the way we think about solving problems. In the least, it has allowed us to dream about what may be possible for this still nascent set of capabilities. Because that's what AIOps truly is — a set of capabilities. In the same way monitoring has evolved into a conversation about observability, automation and data (of all types) have evolved into a conversation about AIOps. And since capabilities are the true gateway to positive business outcomes, it is great to see that — according to the most recent SRE survey — reliability practitioners believe AIOPs will make their work easier (52%), while not replacing them (4%)," says Leo Vasiliou, Director of Product Marketing at Catchpoint.

Image removed.

"I believe that most of this technology will be in the form of a very intelligent assistant, rather than replace humans in the loop. I do think it will help eliminate a lot of the groundwork and help teams be more effective and faster in remediating problems," adds Spiros Xanthos, SVP and General Manager of Observability at Splunk.

Complementing Observability

"Observability plays a vital role, working hand-in-hand with AIOps to form a powerful combination, which complements and reinforces each other. An organization equipped with both can leverage AIOps for more intelligent and dynamic monitoring, featuring anomaly detection and advanced root cause analysis," says Siddiqui from BMC.

AIOps for Each Vertical

"People tend to only think about it in the context of alerting or applying CI/CD techniques to IT, but you can also see AIOps techniques applied across various industries and use cases. Health organizations used AIOps to report on COVID data that they collected from a variety of databases in different formats, for example. There are many more opportunities to apply AIOps to core business functions, and eventually engineering functions, too," says Camden Swita, Senior Product Manager at New Relic.

"There will be AIOps technology tailored for every vertical — retail, manufacturing, financial services, utilities, etc. These systems will train on machine data unique to each sector, so they'll offer more specific intelligence and insights," Monika Bhave, Product Manager at Digitate, predicts.

Generative AI Improves AIOps

"Generative AI will make AIOps better as complex orchestrations, automations, etc. will leverage natural language processing or other methods to better interact with what can be complex tooling," says Heath Newburn, Distinguished Field Engineer at PagerDuty.

Natural Language Interfaces

Carlos Casanova from Forrester says, "I see AIOps solutions having much more sophisticated Natural Language Interfaces (NLI) such that lower skilled/trained individuals can perform higher level work. This will hopefully offset some of the displacement that the automation is bringing."

"The next generation of AIOps platforms will offer some form of natural language processing interactions as a way to quickly ramp up a knowledge base that is easily understood by users," Thomas LaRock, Principal Developer Evangelist at Selector, agrees. "This is in contrast to legacy systems which rely on manual help files compiled by subject matter experts and need constant revisions. As AIOps continues to mature and become easier to implement as well as utilize, it will spread to every corner of the office in much the same way the Internet did 30 years ago — gradually, then suddenly."

Variety of Personas

"I see a scenario where the vendor's technologies are able to engage a variety of personas from service delivery, to engineering, to security to business owner," Carlos Casanova from Forrester envisions. "If the data is all the same from across the enterprise, there's no reason why there should be a multitude of tools segmented by persona. I speak to the current state of this from just the technology side in my Three Stages of Preparation For AIOps report. Picking your perspective is the first step."

Read the Forrester blog: Perspective Is Key To Understanding AIOps

Delivering on the Promise

"I think the future of AIOps is people actually doing AIOps. The AIOps space is at the peak of inflated expectations on the hype curve. I don't think people have realized value from AIOps in a meaningful way yet, so the future is about actually applying it. The future of AIOps is about delivering on its own productivity promise," says Bill Lobig, VP Product Management of Automation at IBM.

"AIOps gives the enterprise greater command over its monitored environment so the enterprise can adapt faster and with greater confidence. As enterprises adopt new technologies, rely increasingly on complex digital services to deliver value to customers and seek to connect IT organizations with business outcomes, AIOPs will be an important catalyst for change," Andreas Reiss, Head of Product Management, AIOps and Observability, at Broadcom, concludes. "Where that will lead is tremendously exciting."

Auto-Remediation

Probably the most important ultimate vision, and hope, for AIOps is auto-remediation.

“The movement toward higher levels of automation including automated remediation is accelerating. Typically this can be done on two levels — automated remediation requiring initial IT approval, and automated remediation that occurs on its own, but which should also document its actions in some way. There is definitely a move toward the latter, as both business and technology dynamics are becoming more accelerated,” says Dennis Drogseth, VP at Enterprise Management Associates (EMA).

Go to: Discovering AIOps - Part 9: Auto-Remediation

Pete Goldin is Editor and Publisher of APMdigest

Hot Topics

The Latest

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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 ...