2024 Application Performance Management Predictions - Part 6: AIOps and ITSM

Industry experts offer thoughtful, insightful, and often controversial predictions on how APM, AIOps, Observability, OpenTelemetry and related technologies will evolve and impact business in 2024. Part 6 covers AIOps and ITSM.

Start with: 2024 Application Performance Management Predictions - Part 1

Start with: 2024 Application Performance Management Predictions - Part 2

Start with: 2024 Application Performance Management Predictions - Part 3

Start with: 2024 Application Performance Management Predictions - Part 4

Start with: 2024 Application Performance Management Predictions - Part 5

MEANING OF AIOPS BECOMES INCREASINGLY CONFUSING

Just what AIOps means will increasingly become a source of confusion, as market definitions seek to confine a diversity of solutions which vary in scope, design point, use case, complexity, and value into a single consistent box. Buyers will need to look for the fit that's right for them, not linear winners in a non-linear set of options.
Dennis Drogseth
VP, Enterprise Management Associates (EMA)

AIOPS DOES NOT REACH DREAM STATE NEXT YEAR

AIOps, in the truest sense, is currently more like a pipe dream or goal state for most companies. I don't expect the industry to reach the dream state of AIOps next year; however, I think we'll see significant progress and investments in the AIOps space. In the not-too-distant future, an engineer is going to have the ability to respond to an incident, get a highly detailed summary—explaining what the problem is, if it's occurred before, if it appears to be novel, etc—and gain solid suggestions on what they should do to remediate the issue, with specific suggestions like rolling back the deployment or updating the configuration. Plus, with the improvements to generative AI over the next few years, these suggestions could very well include the new code or the updated configuration itself. Even so, we won't be quite to the point where an Ops person is going to be able to just sleep through the incident, but the industry is heading in that direction.
Camden Swita
Senior Product Manager, New Relic

AIOPS FALLS OUT FAVOR

AIOps will continue to fall out of favor as those that implemented it realize that the promised benefits like root cause detection just aren't there.
Jeremy Burton
CEO, Observe

SHIFT FROM AIOPS TO LLMs

In 2024, I expect to see more companies reach a breaking point with AIOps and shift their focus towards the potential of LLMs. While AIOps was a laudable concept when introduced, in practice it has failed to live up to its promise. The idea that you could train a model on data emitted by apps, that change every day, is nothing more than a pipe dream. Large Language Models (LLMs) appear to be a far more promising alternative because they attack the problem differently and help users make more intelligent decisions. Companies are waking up to this fact but many more will begin to act on it in the new year.
Jeremy Burton
CEO, Observe

FUSION OF AIOPS AND CONTAINERS REDEFINES ITOPS

The fusion of AIOps with container technology is set to redefine IT operations. This integration promises to catalyze a shift from reactive to predictive management, harnessing intelligent automation to anticipate issues before they impact performance. While high-performance computing (HPC) has traditionally been cautious in adopting such trends, we anticipate a growing recognition of their value in driving efficiency and reliability across all sectors of IT operations, including high-performance environments.
Keith Cunningham
VP of Strategy, Sylabs

USAGE METERING CRITICAL FOR AIOPS

Usage metering will become critical to companies leveraging AIOps due to its user-level granularity and unique insights. To get ahead of this, businesses should instrument usage metering as soon as possible. Accurate usage data is invaluable to understanding your customers, training your AIOps models, and gleaning insights across various business functions.
Puneet Gupta
CEO and Founder, Amberflo

AIOPS EXPANDS BEYOND ITOPS

AIOps will expand beyond its traditional definition of IT operations as other business units will consider applying advanced analytics to their growing piles of data.
Thomas LaRock
Principal Developer Evangelist, Selector.AI

WORKING TOWARDS ITSM POTENTIAL

Similarly to AIOps, the industry is working toward reaching the full potential of ITSM. Eventually, these capabilities will empower engineering teams to automate tasks, like identifying incidents before they reach a critical state, applying changes to remediate issues before they become serious, or writing and resolving support tickets.
Camden Swita
Senior Product Manager, New Relic

ITSM LEVERAGES GENAI INTERACTIONS

IT Service Management (ITSM) will experience a trending adoption of ChatGPT-like interactions for end-users to easily get answers to today's help desk scenarios. Organizations will look to adopt this as well to reduce operational costs.
Zubaid Kazmi
Managing Director, Identity and Access Management, MorganFranklin Consulting

ITSM TEAMS INVEST IN EMPLOYEE EXPERIENCE MANAGEMENT

ITSM teams will invest in employee experience management tools to minimize digital friction and to proactively address issues with connectivity and application performance from the user perspective for both distributed remote and in-office employees. We'll seen an uptick in understanding and mapping user journeys so organizations can best tailor digital experiences to individual preferences.
Gerardo Dada
CMO, Catchpoint

Image removed.

DIGITAL ADOPTION PLATFORMS SUPPORT ITSM

Given the staggering cost of software application downtime — which runs at about $5,600 per minute — in 2024, we expect to see more organizations embracing a digital adoption platform (DAP) in tandem with their ITSM strategy. We increasingly see IT managers taking this step to avoid expensive downtime when a disruption occurs. The key is to have ongoing training, automation or guided risk management processes in place so there is little to no pause in response when the inevitable happens.
Krishna Dunthoori
Founder and CEO, Apty

Go to: 2024 Application Performance Management Predictions - Part 7, covering the user experience.

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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 ...

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2024 Application Performance Management Predictions - Part 6: AIOps and ITSM

Industry experts offer thoughtful, insightful, and often controversial predictions on how APM, AIOps, Observability, OpenTelemetry and related technologies will evolve and impact business in 2024. Part 6 covers AIOps and ITSM.

Start with: 2024 Application Performance Management Predictions - Part 1

Start with: 2024 Application Performance Management Predictions - Part 2

Start with: 2024 Application Performance Management Predictions - Part 3

Start with: 2024 Application Performance Management Predictions - Part 4

Start with: 2024 Application Performance Management Predictions - Part 5

MEANING OF AIOPS BECOMES INCREASINGLY CONFUSING

Just what AIOps means will increasingly become a source of confusion, as market definitions seek to confine a diversity of solutions which vary in scope, design point, use case, complexity, and value into a single consistent box. Buyers will need to look for the fit that's right for them, not linear winners in a non-linear set of options.
Dennis Drogseth
VP, Enterprise Management Associates (EMA)

AIOPS DOES NOT REACH DREAM STATE NEXT YEAR

AIOps, in the truest sense, is currently more like a pipe dream or goal state for most companies. I don't expect the industry to reach the dream state of AIOps next year; however, I think we'll see significant progress and investments in the AIOps space. In the not-too-distant future, an engineer is going to have the ability to respond to an incident, get a highly detailed summary—explaining what the problem is, if it's occurred before, if it appears to be novel, etc—and gain solid suggestions on what they should do to remediate the issue, with specific suggestions like rolling back the deployment or updating the configuration. Plus, with the improvements to generative AI over the next few years, these suggestions could very well include the new code or the updated configuration itself. Even so, we won't be quite to the point where an Ops person is going to be able to just sleep through the incident, but the industry is heading in that direction.
Camden Swita
Senior Product Manager, New Relic

AIOPS FALLS OUT FAVOR

AIOps will continue to fall out of favor as those that implemented it realize that the promised benefits like root cause detection just aren't there.
Jeremy Burton
CEO, Observe

SHIFT FROM AIOPS TO LLMs

In 2024, I expect to see more companies reach a breaking point with AIOps and shift their focus towards the potential of LLMs. While AIOps was a laudable concept when introduced, in practice it has failed to live up to its promise. The idea that you could train a model on data emitted by apps, that change every day, is nothing more than a pipe dream. Large Language Models (LLMs) appear to be a far more promising alternative because they attack the problem differently and help users make more intelligent decisions. Companies are waking up to this fact but many more will begin to act on it in the new year.
Jeremy Burton
CEO, Observe

FUSION OF AIOPS AND CONTAINERS REDEFINES ITOPS

The fusion of AIOps with container technology is set to redefine IT operations. This integration promises to catalyze a shift from reactive to predictive management, harnessing intelligent automation to anticipate issues before they impact performance. While high-performance computing (HPC) has traditionally been cautious in adopting such trends, we anticipate a growing recognition of their value in driving efficiency and reliability across all sectors of IT operations, including high-performance environments.
Keith Cunningham
VP of Strategy, Sylabs

USAGE METERING CRITICAL FOR AIOPS

Usage metering will become critical to companies leveraging AIOps due to its user-level granularity and unique insights. To get ahead of this, businesses should instrument usage metering as soon as possible. Accurate usage data is invaluable to understanding your customers, training your AIOps models, and gleaning insights across various business functions.
Puneet Gupta
CEO and Founder, Amberflo

AIOPS EXPANDS BEYOND ITOPS

AIOps will expand beyond its traditional definition of IT operations as other business units will consider applying advanced analytics to their growing piles of data.
Thomas LaRock
Principal Developer Evangelist, Selector.AI

WORKING TOWARDS ITSM POTENTIAL

Similarly to AIOps, the industry is working toward reaching the full potential of ITSM. Eventually, these capabilities will empower engineering teams to automate tasks, like identifying incidents before they reach a critical state, applying changes to remediate issues before they become serious, or writing and resolving support tickets.
Camden Swita
Senior Product Manager, New Relic

ITSM LEVERAGES GENAI INTERACTIONS

IT Service Management (ITSM) will experience a trending adoption of ChatGPT-like interactions for end-users to easily get answers to today's help desk scenarios. Organizations will look to adopt this as well to reduce operational costs.
Zubaid Kazmi
Managing Director, Identity and Access Management, MorganFranklin Consulting

ITSM TEAMS INVEST IN EMPLOYEE EXPERIENCE MANAGEMENT

ITSM teams will invest in employee experience management tools to minimize digital friction and to proactively address issues with connectivity and application performance from the user perspective for both distributed remote and in-office employees. We'll seen an uptick in understanding and mapping user journeys so organizations can best tailor digital experiences to individual preferences.
Gerardo Dada
CMO, Catchpoint

Image removed.

DIGITAL ADOPTION PLATFORMS SUPPORT ITSM

Given the staggering cost of software application downtime — which runs at about $5,600 per minute — in 2024, we expect to see more organizations embracing a digital adoption platform (DAP) in tandem with their ITSM strategy. We increasingly see IT managers taking this step to avoid expensive downtime when a disruption occurs. The key is to have ongoing training, automation or guided risk management processes in place so there is little to no pause in response when the inevitable happens.
Krishna Dunthoori
Founder and CEO, Apty

Go to: 2024 Application Performance Management Predictions - Part 7, covering the user experience.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

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 ...

Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

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 ...

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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 ...

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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 ...