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AI Shines Bright in APM, But Challenges Remain

Sudhir Jha

Performance management of enterprise applications is key to achieving business objectives and maximizing returns on IT investments. But with increasing system complexity, rapidly evolving platforms, shorter time to market and inadequate quantitative models and tools, performance management often represents one of the most challenging aspects for enterprise IT.

The hype around artificial intelligence (AI) is beginning to settle, and companies are beginning to see measurable change from early investments in the technology. This initial success, however nascent, is silencing some of the doubt that AI would be able to deliver on its promise.

The deluge of data created by IT infrastructures that generate data every second often takes great investments of time to make sense of. Leveraging AI or machine learning technologies in Application Performance Management (APM) simplifies the complex IT systems, automates application-environment discovery and makes for smarter decisions faster with proactive problem resolution. The benefits of AI-driven APM solutions seem obvious but raise important questions around AI technologies and its greater impact.

To better understand the state of AI among enterprises across industries, Infosys commissioned a survey of more than 1,000 global C-level executives and IT decision makers (ITDMs). The survey focused on the impact AI deployments are having on organizations and reveals the return on investment (ROI) of current AI deployments, as well as its impact on leadership and the workforce.

The research, Leadership in the Age of AI Report, makes clear that AI technologies are no longer experimental, rather they are already broadly deployed, producing real results and impacting business strategy, IT investments, and the workforce.

AI Beyond Automation

The research found that 86 percent of organizations surveyed have middle or late-stage AI deployments and view AI as a major facilitator of future business operations.

Nine out of 10 C-level executives reported measurable benefits from AI within their organizations.

AI is dependent upon data quality and accessibility, making APM a critical underpinning to success of AI initiatives. AI is not a standalone application but part of a knowledge management ecosystem that involves layers of business and IT data. Machine learning, computer vision, and automated reasoning and other technologies may be part of that ecosystem.


The survey found the top strategic advantages organizations report from their AI deployments are improved process performance (45 percent), productivity gains due to IT time spent on higher-value work (40 percent) or related to fewer staff needed to accomplish analogous workloads (38 percent), improved compliance, security and risk management (38 percent).

But the positive effects of AI within organizations go beyond driving efficiencies, as three-fourths of C-level executives said they expect AI to impact their organization's offerings even more than they would impact organizational processes.

The research also showed that the majority of organizations start off using AI to automate or improve routine or inefficient processes with 66 percent of organizations primarily leveraging AI for business process automation.

When looking at companies with later stage AI deployments, 80 percent of IT decision makers (ITDMs) reported they are using AI to augment existing solutions or build new business-critical solutions and services to optimize insights and the consumer experience. Here, APM can play a significant role in how these insights are derived.

Challenges in the Age of AI

AI may end up being a boon to APM solutions — but that's not to say there won't be challenges to address in the new age of AI. Companies need to ensure that their most important investment, their people, are prepared for a future fueled by automation and are equipped with the necessary skills for the new roles AI will create. Additionally, companies need to provide the necessary resources and time to support the learning curve that comes with these technologies.

IT has been the primary focus of AI initiatives, and will continue to be for the foreseeable future. The survey found 61 percent of respondents agreed that IT will be the most impacted job function over the next five years. As IT departments continue to implement AI-based tools, they will become imperative for modern IT operations.

Similar to APM solutions, data largely underpins the successful use of AI. Another challenge important to note as the age of AI takes hold is 49 percent of respondents reported that their organization is unable to deploy the AI technologies they want because their data is not ready to support them. As such, 77 percent of ITDMs reported they plan to invest in data management.

Artificial Intelligence is rapidly being adopted by companies across industries and most would agree that it holds the potential to unlock benefits currently untapped by existing IT. So far, the arc of AI leans toward empowerment and giving IT and business organizations the tools necessary to automate redundant tasks, detect and analyze hidden patterns in data and generally make possible revolutionary insights that will help achieve objectives.

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For years, the success of DevOps has been measured by how much manual work teams can automate ... I believe that in 2026, the definition of DevOps success is going to expand significantly. The era of automation is giving way to the era of intelligent delivery, in which AI doesn't just accelerate pipelines, it understands them. With open observability connecting signals end-to-end across those tools, teams can build closed-loop systems that don't just move faster, but learn, adapt, and take action autonomously with confidence ...

The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points ...

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

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APMdigest's Predictions Series continues with 2026 Data Center Predictions — industry experts offer predictions on how data centers will evolve and impact business in 2026 ...

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AI Shines Bright in APM, But Challenges Remain

Sudhir Jha

Performance management of enterprise applications is key to achieving business objectives and maximizing returns on IT investments. But with increasing system complexity, rapidly evolving platforms, shorter time to market and inadequate quantitative models and tools, performance management often represents one of the most challenging aspects for enterprise IT.

The hype around artificial intelligence (AI) is beginning to settle, and companies are beginning to see measurable change from early investments in the technology. This initial success, however nascent, is silencing some of the doubt that AI would be able to deliver on its promise.

The deluge of data created by IT infrastructures that generate data every second often takes great investments of time to make sense of. Leveraging AI or machine learning technologies in Application Performance Management (APM) simplifies the complex IT systems, automates application-environment discovery and makes for smarter decisions faster with proactive problem resolution. The benefits of AI-driven APM solutions seem obvious but raise important questions around AI technologies and its greater impact.

To better understand the state of AI among enterprises across industries, Infosys commissioned a survey of more than 1,000 global C-level executives and IT decision makers (ITDMs). The survey focused on the impact AI deployments are having on organizations and reveals the return on investment (ROI) of current AI deployments, as well as its impact on leadership and the workforce.

The research, Leadership in the Age of AI Report, makes clear that AI technologies are no longer experimental, rather they are already broadly deployed, producing real results and impacting business strategy, IT investments, and the workforce.

AI Beyond Automation

The research found that 86 percent of organizations surveyed have middle or late-stage AI deployments and view AI as a major facilitator of future business operations.

Nine out of 10 C-level executives reported measurable benefits from AI within their organizations.

AI is dependent upon data quality and accessibility, making APM a critical underpinning to success of AI initiatives. AI is not a standalone application but part of a knowledge management ecosystem that involves layers of business and IT data. Machine learning, computer vision, and automated reasoning and other technologies may be part of that ecosystem.


The survey found the top strategic advantages organizations report from their AI deployments are improved process performance (45 percent), productivity gains due to IT time spent on higher-value work (40 percent) or related to fewer staff needed to accomplish analogous workloads (38 percent), improved compliance, security and risk management (38 percent).

But the positive effects of AI within organizations go beyond driving efficiencies, as three-fourths of C-level executives said they expect AI to impact their organization's offerings even more than they would impact organizational processes.

The research also showed that the majority of organizations start off using AI to automate or improve routine or inefficient processes with 66 percent of organizations primarily leveraging AI for business process automation.

When looking at companies with later stage AI deployments, 80 percent of IT decision makers (ITDMs) reported they are using AI to augment existing solutions or build new business-critical solutions and services to optimize insights and the consumer experience. Here, APM can play a significant role in how these insights are derived.

Challenges in the Age of AI

AI may end up being a boon to APM solutions — but that's not to say there won't be challenges to address in the new age of AI. Companies need to ensure that their most important investment, their people, are prepared for a future fueled by automation and are equipped with the necessary skills for the new roles AI will create. Additionally, companies need to provide the necessary resources and time to support the learning curve that comes with these technologies.

IT has been the primary focus of AI initiatives, and will continue to be for the foreseeable future. The survey found 61 percent of respondents agreed that IT will be the most impacted job function over the next five years. As IT departments continue to implement AI-based tools, they will become imperative for modern IT operations.

Similar to APM solutions, data largely underpins the successful use of AI. Another challenge important to note as the age of AI takes hold is 49 percent of respondents reported that their organization is unable to deploy the AI technologies they want because their data is not ready to support them. As such, 77 percent of ITDMs reported they plan to invest in data management.

Artificial Intelligence is rapidly being adopted by companies across industries and most would agree that it holds the potential to unlock benefits currently untapped by existing IT. So far, the arc of AI leans toward empowerment and giving IT and business organizations the tools necessary to automate redundant tasks, detect and analyze hidden patterns in data and generally make possible revolutionary insights that will help achieve objectives.

Hot Topics

The Latest

Payment system failures are putting $44.4 billion in US retail and hospitality sales at risk each year, underscoring how quickly disruption can derail day-to-day trading, according to research conducted by Dynatrace ... The findings show that payment failures are no longer isolated incidents, but part of a recurring operational challenge that disrupts service, damages customer trust, and negatively impacts revenue ...

For years, the success of DevOps has been measured by how much manual work teams can automate ... I believe that in 2026, the definition of DevOps success is going to expand significantly. The era of automation is giving way to the era of intelligent delivery, in which AI doesn't just accelerate pipelines, it understands them. With open observability connecting signals end-to-end across those tools, teams can build closed-loop systems that don't just move faster, but learn, adapt, and take action autonomously with confidence ...

The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points ...

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment ...

My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

APMdigest's Predictions Series continues with 2026 Data Center Predictions — industry experts offer predictions on how data centers will evolve and impact business in 2026 ...

APMdigest's Predictions Series continues with 2026 DataOps Predictions — industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2026. Part 2 covers data and data platforms ...