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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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APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

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

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...