Discovering AIOps - Part 5: More Advantages

Pete Goldin
APMdigest

In Part 4 of this blog series, the experts show that AIOps offers some very compelling advantages. Part 5 covers additional expert picks for the advantages that can be gained from AIOps, especially from the business perspective.

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

Reduced Outages

"Adopting AIOps reduces outages for businesses and speeds up the ability to predict and prevent outages before they happen; as such, users should look for an AIOps provider that can improve the time it takes to remediate outages and improve overall customer experience," says Spiros Xanthos, SVP and General Manager of Observability at Splunk.

Improved Operational Resilience

"When well deployed, AIOps not only reduces the length and impact of downtime, but gives us insights on how to create better operational resilience," says Heath Newburn, Distinguished Field Engineer at PagerDuty.

Improved Customer and Employee Experience

"From a business perspective, user, customer and employee experience can be greatly improved from the proactive posture that AIOps enables," says Carlos Casanova, Principal Analyst at Forrester Research.

"Without AIOps, outages that leave a negative impact on performance and reliability may arise, potentially directly impacting revenue and tarnishing brand equity," Xanthos from Splunk comments.

By delivering better availability with shorter outages, customer experience should improve and the associated customer satisfaction (CSAT) and Net Promoter Score (NPS) can increase, adds Newburn from PagerDuty.

"While the IT shop might be winning because it is meeting its SLOs for systems downtime, the larger outcome is that this is improving customer experience, or preventing lost revenue, and that's of course a major impact for the entire organization," Asaf Yigal, CTO of Logz.io asserts.

"AIOps can correlate technical problems to business outcomes and end user experiences. That's the Holy Grail of monitoring that AIOPs achieves," says Andreas Reiss, Head of Product Management, AIOps and Observability, at Broadcom.

"C-levels are using AIOps-supported metrics to understand and manage key business performance indicators. For today's software-fueled businesses, this is just inevitably the value at a certain point," adds Yigal from Logz.io.

Increased IT Productivity

"Since AIOps helps to detect anomalous behaviors unseen by human operators, there is decreased risk to the business, which means IT teams have more bandwidth to help with initiatives that are forward looking, instead of being burdened by manual correlation and firefighting high volumes of alerts," says Michael Gerstenhaber, VP of Product Management at Datadog.

Bob Wambach, VP of Product Marketing at Dynatrace, adds, "We expect AIOps to enable IT teams to do more with their time, cutting out the manual, laborious intervention needed to keep applications secure. AIOps will free up more time for innovation and problem resolution."

Monika Bhave, Product Manager at Digitate, agrees that with AIOps, IT teams are free to work on projects that deliver new business value and ultimately help support revenue growth, such as implementing new software, migrating to the cloud, driving digital transformation efforts, and expediting onboarding/offboarding procedures.

Improved Development Process and Developer Experience

"By reducing the time spent in break/fix and chasing down problems, teams can focus on reducing development cycles and improving feature velocity, adding to the improvements described above, but also improving developer experience, and with the reduction of alert fatigue improving morale and reducing developer turnover," says Newburn of PagerDuty.

Cost Optimization

"AIOps helps organizations achieve cost savings by improving operational efficiency and increased productivity, and by reducing downtime which minimizes the associated costs of disruptions to business operations," says Gerstenhaber from Datadog.

AIOps also delivers cost optimization by enhancing resource allocation and utilization, explains Payal Kindiger, Senior Director of Product Marketing at Riverbed. By analyzing data patterns and resource demands, AIOps helps businesses avoid over-provisioning while ensuring that resources are optimally allocated, resulting in significant cost savings.

Enabling Adoption of Advanced Technologies

In addition to all the advantages outlined in Part 4 and Part 5 of this blog series, the experts say that AIOps also provides a more forward-thinking advantage: empowering organizations to more easily and effectively adopt advanced technologies, such as microservices, containers and hybrid cloud.

Until recently, IT operations teams have had few options when it comes to tackling the expanding complexity of vital technologies, says Brian Emerson, VP & GM, IT Operations Management at ServiceNow.

Modern applications are built from hundreds or thousands of interdependent microservices distributed across multiple clouds, creating incredibly complex software environments, explains Wambach from Dynatrace. This complexity makes it difficult for IT pros to understand the state of these systems, especially when something goes wrong.

Camden Swita, Senior Product Manager at New Relic says consider this: "If it's hard for humans to keep an eye on 'traditional' or simple IT infrastructures and app architectures, it's literally impossible for them to do so for newer versions. The sheer number of 'entities' prohibits human monitoring and challenges our reasoning abilities. You'd be hard-pressed to adequately monitor and triage newer infras and architectures without the assistance of AIOps."

"The dynamic nature of hybrid cloud, microservices, and container environments can lead to increased complexity and challenges in monitoring and managing them effectively," Bharani Kumar Kulasekaran, Product Manager at ManageEngine, agrees. "AIOps platforms help navigate the scale and intricacies of these architectures by providing better visibility and a more holistic view into these environments. By delivering real-time insights obtained from the infrastructure data, AIOps helps optimize resource allocation, ensure performance, and maintain availability across dynamic environments, ultimately resulting in smoother adoption and management of advanced IT infrastructures."

Ali Siddiqui, Chief Product Officer at BMC, concludes, "By adopting AIOps, organizations can confidently embrace new application architectures and navigate increasingly complex hybrid ecosystems while ensuring seamless alignment with the evolving needs of the business and customer demands."

Go to: Discovering AIOps - Part 6, covering the challenges of AIOps.

Pete Goldin is Editor and Publisher of APMdigest

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Discovering AIOps - Part 5: More Advantages

Pete Goldin
APMdigest

In Part 4 of this blog series, the experts show that AIOps offers some very compelling advantages. Part 5 covers additional expert picks for the advantages that can be gained from AIOps, especially from the business perspective.

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

Reduced Outages

"Adopting AIOps reduces outages for businesses and speeds up the ability to predict and prevent outages before they happen; as such, users should look for an AIOps provider that can improve the time it takes to remediate outages and improve overall customer experience," says Spiros Xanthos, SVP and General Manager of Observability at Splunk.

Improved Operational Resilience

"When well deployed, AIOps not only reduces the length and impact of downtime, but gives us insights on how to create better operational resilience," says Heath Newburn, Distinguished Field Engineer at PagerDuty.

Improved Customer and Employee Experience

"From a business perspective, user, customer and employee experience can be greatly improved from the proactive posture that AIOps enables," says Carlos Casanova, Principal Analyst at Forrester Research.

"Without AIOps, outages that leave a negative impact on performance and reliability may arise, potentially directly impacting revenue and tarnishing brand equity," Xanthos from Splunk comments.

By delivering better availability with shorter outages, customer experience should improve and the associated customer satisfaction (CSAT) and Net Promoter Score (NPS) can increase, adds Newburn from PagerDuty.

"While the IT shop might be winning because it is meeting its SLOs for systems downtime, the larger outcome is that this is improving customer experience, or preventing lost revenue, and that's of course a major impact for the entire organization," Asaf Yigal, CTO of Logz.io asserts.

"AIOps can correlate technical problems to business outcomes and end user experiences. That's the Holy Grail of monitoring that AIOPs achieves," says Andreas Reiss, Head of Product Management, AIOps and Observability, at Broadcom.

"C-levels are using AIOps-supported metrics to understand and manage key business performance indicators. For today's software-fueled businesses, this is just inevitably the value at a certain point," adds Yigal from Logz.io.

Increased IT Productivity

"Since AIOps helps to detect anomalous behaviors unseen by human operators, there is decreased risk to the business, which means IT teams have more bandwidth to help with initiatives that are forward looking, instead of being burdened by manual correlation and firefighting high volumes of alerts," says Michael Gerstenhaber, VP of Product Management at Datadog.

Bob Wambach, VP of Product Marketing at Dynatrace, adds, "We expect AIOps to enable IT teams to do more with their time, cutting out the manual, laborious intervention needed to keep applications secure. AIOps will free up more time for innovation and problem resolution."

Monika Bhave, Product Manager at Digitate, agrees that with AIOps, IT teams are free to work on projects that deliver new business value and ultimately help support revenue growth, such as implementing new software, migrating to the cloud, driving digital transformation efforts, and expediting onboarding/offboarding procedures.

Improved Development Process and Developer Experience

"By reducing the time spent in break/fix and chasing down problems, teams can focus on reducing development cycles and improving feature velocity, adding to the improvements described above, but also improving developer experience, and with the reduction of alert fatigue improving morale and reducing developer turnover," says Newburn of PagerDuty.

Cost Optimization

"AIOps helps organizations achieve cost savings by improving operational efficiency and increased productivity, and by reducing downtime which minimizes the associated costs of disruptions to business operations," says Gerstenhaber from Datadog.

AIOps also delivers cost optimization by enhancing resource allocation and utilization, explains Payal Kindiger, Senior Director of Product Marketing at Riverbed. By analyzing data patterns and resource demands, AIOps helps businesses avoid over-provisioning while ensuring that resources are optimally allocated, resulting in significant cost savings.

Enabling Adoption of Advanced Technologies

In addition to all the advantages outlined in Part 4 and Part 5 of this blog series, the experts say that AIOps also provides a more forward-thinking advantage: empowering organizations to more easily and effectively adopt advanced technologies, such as microservices, containers and hybrid cloud.

Until recently, IT operations teams have had few options when it comes to tackling the expanding complexity of vital technologies, says Brian Emerson, VP & GM, IT Operations Management at ServiceNow.

Modern applications are built from hundreds or thousands of interdependent microservices distributed across multiple clouds, creating incredibly complex software environments, explains Wambach from Dynatrace. This complexity makes it difficult for IT pros to understand the state of these systems, especially when something goes wrong.

Camden Swita, Senior Product Manager at New Relic says consider this: "If it's hard for humans to keep an eye on 'traditional' or simple IT infrastructures and app architectures, it's literally impossible for them to do so for newer versions. The sheer number of 'entities' prohibits human monitoring and challenges our reasoning abilities. You'd be hard-pressed to adequately monitor and triage newer infras and architectures without the assistance of AIOps."

"The dynamic nature of hybrid cloud, microservices, and container environments can lead to increased complexity and challenges in monitoring and managing them effectively," Bharani Kumar Kulasekaran, Product Manager at ManageEngine, agrees. "AIOps platforms help navigate the scale and intricacies of these architectures by providing better visibility and a more holistic view into these environments. By delivering real-time insights obtained from the infrastructure data, AIOps helps optimize resource allocation, ensure performance, and maintain availability across dynamic environments, ultimately resulting in smoother adoption and management of advanced IT infrastructures."

Ali Siddiqui, Chief Product Officer at BMC, concludes, "By adopting AIOps, organizations can confidently embrace new application architectures and navigate increasingly complex hybrid ecosystems while ensuring seamless alignment with the evolving needs of the business and customer demands."

Go to: Discovering AIOps - Part 6, covering the challenges of AIOps.

Pete Goldin is Editor and Publisher of APMdigest

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" ...

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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 ...

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