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

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Manufacturing Organizations Doubled AI Investment Yet Only 37% Fully Prepared to Operationalize AI

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Optimizing Decisions with Edge-First Cognitive Intelligence

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

The New Perimeter Is the User: Why Identity Is the Real Network Edge

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

When AI Infrastructure Stops Behaving Like Infrastructure

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Enterprise Resilience: Understanding the Shift from Static to Dynamic

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile Users Expect Perfection in 2026

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

AI Confidence Is High. Readiness Is Not. What the Data Tells Us - and Why It Matters

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI, Realistic Expectations and the Future of IT Operations in 2026

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

Trust, But Verify: Building Confidence in AI Through Human Oversight

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

Data Centers Plan to Reduce Reliance on Grid

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

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

Manufacturing Organizations Doubled AI Investment Yet Only 37% Fully Prepared to Operationalize AI

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Optimizing Decisions with Edge-First Cognitive Intelligence

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

The New Perimeter Is the User: Why Identity Is the Real Network Edge

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

When AI Infrastructure Stops Behaving Like Infrastructure

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Enterprise Resilience: Understanding the Shift from Static to Dynamic

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile Users Expect Perfection in 2026

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

AI Confidence Is High. Readiness Is Not. What the Data Tells Us - and Why It Matters

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI, Realistic Expectations and the Future of IT Operations in 2026

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

Trust, But Verify: Building Confidence in AI Through Human Oversight

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

Data Centers Plan to Reduce Reliance on Grid

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...