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Today's IT Challenges Identified - and Solved by AIOps

Akhilesh Tripathi
Digitate

The pandemic has spurred organizations to rapidly shift away from traditional in-house IT infrastructures to modern and agile IT systems that support enterprise-wide digital transformation efforts, such as cloud migration and automation enablement. These digital transformation initiatives have been critical to business continuity in the midst of an unprecedented global market upset that came in the form of COVID-19.

Along with the shift to modern and agile IT systems comes an increase in the volume of data created by various digital systems and solutions. Traditional IT management solutions that involve manual efforts for tedious and repeatable processes cannot keep up with the pace of these rapid changes and leaves IT teams facing challenges surrounding infrastructure complexities, long delays in isolating and resolving IT faults, and inconsistent and variable quality of operations.

AI-driven software can help to overcome these challenges by acting as an intelligence tool to assess enterprise system behavior and detect anomalies, resolve IT incidents and even prescribe and proactively take action to prevent the disruption of IT operations.


Below are the findings from the recent Autonomous Enterprise Survey that uncovered trends around the ongoing adoption of artificial intelligence (AI) for IT operations (AIOps) and the technology's benefits to business users.

Today's IT Operational Challenges

To better understand the business and departmental need for AIOps, let's look at the top IT operational challenges organizations face today. The primary challenge organizational IT reported is dealing with too many routine and redundant tasks, with 82% reporting this as their top IT problem. The next biggest challenges were a lack of capabilities to proactively detect and correct system issues, and a need for flexibility to scale with business needs — with 64% of respondents claiming each of these challenges.

The benefits AIOps delivers to businesses perfectly address these current IT challenges. Well-built AIOps solutions leverage advanced AI-based reasoning to detect and correct system issues automatically — simultaneously reducing manual effort spent on managing IT operations by up to 60%. Many businesses recognize these benefits, with 82% reporting that AIOps is necessary for future growth and transformation of businesses.

Qualitative survey responses explained the thought process behind this prioritization of AIOps solutions. The complexity of hybrid and multi-cloud infrastructures, increasing transactional volumes and the criticality of online business systems make it impossible for traditional IT systems to manage every application and infrastructure without automation. The overwhelming amount of data in today's business operations is simply too much for manual analysis.

In addition, the insights provided by AIOps mean the performance of various tasks and decisions can be greatly improved while reducing the manual effort needed to conduct routine tasks — so IT teams can focus on more business-critical tasks that require their immediate attention.

Key Business Drivers for AIOps

There are multiple benefits to AIOps solutions that have significant impacts on an organization's ability to increase revenue and better plan for the future. 91% of organizations identified the removal of manual processes as the most critical benefit, with improved agility and reliability coming in second at 82%. However, AIOps can also support the need to build predictability and resolve problems faster, with 73% identifying this as another key business benefit.

Thanks to AIOps, organizations can adapt to changes fast, and evolve innovative processes that enable sustained growth

The ability to automate rote processes and increase reliability, as well as the ability to better plan for the future are critical to business leaders today, according to a recent PwC survey. Organizations want to give their leadership the confidence that they can remain efficient while withstanding stresses and disruptions. An agile IT operation, supported by AIOps, is an efficient vehicle to achieving resilience in today's constantly evolving, fast-paced business environment. Thanks to AIOps, organizations can adapt to changes fast, and evolve innovative processes that enable sustained growth.

The Obstacles in the Way of AIOps Deployment

With the challenges and benefits of AIOps well addressed and understood, why aren't all companies currently investing in AIOps initiatives?

There are several barriers to adoption, but the biggest obstacle highlighted by 73% of respondents is a lack of experience with intelligent IT solutions.

While this is to be expected for new technologies such as AIOps, as they are still evolving and nascent, organizations should not let it stop them from exploring the possibilities of AIOps further.

In addition, a lack of staffing/talent with appropriate technological skills was identified as a barrier to AIOps adoption by 45% of organizations. That said, digital transformation initiatives happen from the top down. Securing the sponsorship of company leaders is critical to any organizational change, and 55% of organizations claim they lack executive support for, or a strategic approach to, AIOps deployment.

The survey clearly identifies a need for companies to incorporate AIOps, or at the very least intelligent automation, into their organizational culture and strategy to meet the business goals of today's environments as they compound in complexity. AIOps offers a scalable solution to resolve current enterprise IT challenges by automatically detecting, resolving and preventing IT issues. Ultimately, AIOps helps to minimize revenue risk and improve business agility by ensuring zero downtime of critical applications.

However, to properly leverage the full advantages of AIOps, both IT and executive leadership teams must sync their knowledge and understanding of AIOps tools and technology, or risk falling behind their competition.

Akhilesh Tripathi is CEO at Digitate

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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 ...

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 ...

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 ...

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 ...

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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New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

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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Today's IT Challenges Identified - and Solved by AIOps

Akhilesh Tripathi
Digitate

The pandemic has spurred organizations to rapidly shift away from traditional in-house IT infrastructures to modern and agile IT systems that support enterprise-wide digital transformation efforts, such as cloud migration and automation enablement. These digital transformation initiatives have been critical to business continuity in the midst of an unprecedented global market upset that came in the form of COVID-19.

Along with the shift to modern and agile IT systems comes an increase in the volume of data created by various digital systems and solutions. Traditional IT management solutions that involve manual efforts for tedious and repeatable processes cannot keep up with the pace of these rapid changes and leaves IT teams facing challenges surrounding infrastructure complexities, long delays in isolating and resolving IT faults, and inconsistent and variable quality of operations.

AI-driven software can help to overcome these challenges by acting as an intelligence tool to assess enterprise system behavior and detect anomalies, resolve IT incidents and even prescribe and proactively take action to prevent the disruption of IT operations.


Below are the findings from the recent Autonomous Enterprise Survey that uncovered trends around the ongoing adoption of artificial intelligence (AI) for IT operations (AIOps) and the technology's benefits to business users.

Today's IT Operational Challenges

To better understand the business and departmental need for AIOps, let's look at the top IT operational challenges organizations face today. The primary challenge organizational IT reported is dealing with too many routine and redundant tasks, with 82% reporting this as their top IT problem. The next biggest challenges were a lack of capabilities to proactively detect and correct system issues, and a need for flexibility to scale with business needs — with 64% of respondents claiming each of these challenges.

The benefits AIOps delivers to businesses perfectly address these current IT challenges. Well-built AIOps solutions leverage advanced AI-based reasoning to detect and correct system issues automatically — simultaneously reducing manual effort spent on managing IT operations by up to 60%. Many businesses recognize these benefits, with 82% reporting that AIOps is necessary for future growth and transformation of businesses.

Qualitative survey responses explained the thought process behind this prioritization of AIOps solutions. The complexity of hybrid and multi-cloud infrastructures, increasing transactional volumes and the criticality of online business systems make it impossible for traditional IT systems to manage every application and infrastructure without automation. The overwhelming amount of data in today's business operations is simply too much for manual analysis.

In addition, the insights provided by AIOps mean the performance of various tasks and decisions can be greatly improved while reducing the manual effort needed to conduct routine tasks — so IT teams can focus on more business-critical tasks that require their immediate attention.

Key Business Drivers for AIOps

There are multiple benefits to AIOps solutions that have significant impacts on an organization's ability to increase revenue and better plan for the future. 91% of organizations identified the removal of manual processes as the most critical benefit, with improved agility and reliability coming in second at 82%. However, AIOps can also support the need to build predictability and resolve problems faster, with 73% identifying this as another key business benefit.

Thanks to AIOps, organizations can adapt to changes fast, and evolve innovative processes that enable sustained growth

The ability to automate rote processes and increase reliability, as well as the ability to better plan for the future are critical to business leaders today, according to a recent PwC survey. Organizations want to give their leadership the confidence that they can remain efficient while withstanding stresses and disruptions. An agile IT operation, supported by AIOps, is an efficient vehicle to achieving resilience in today's constantly evolving, fast-paced business environment. Thanks to AIOps, organizations can adapt to changes fast, and evolve innovative processes that enable sustained growth.

The Obstacles in the Way of AIOps Deployment

With the challenges and benefits of AIOps well addressed and understood, why aren't all companies currently investing in AIOps initiatives?

There are several barriers to adoption, but the biggest obstacle highlighted by 73% of respondents is a lack of experience with intelligent IT solutions.

While this is to be expected for new technologies such as AIOps, as they are still evolving and nascent, organizations should not let it stop them from exploring the possibilities of AIOps further.

In addition, a lack of staffing/talent with appropriate technological skills was identified as a barrier to AIOps adoption by 45% of organizations. That said, digital transformation initiatives happen from the top down. Securing the sponsorship of company leaders is critical to any organizational change, and 55% of organizations claim they lack executive support for, or a strategic approach to, AIOps deployment.

The survey clearly identifies a need for companies to incorporate AIOps, or at the very least intelligent automation, into their organizational culture and strategy to meet the business goals of today's environments as they compound in complexity. AIOps offers a scalable solution to resolve current enterprise IT challenges by automatically detecting, resolving and preventing IT issues. Ultimately, AIOps helps to minimize revenue risk and improve business agility by ensuring zero downtime of critical applications.

However, to properly leverage the full advantages of AIOps, both IT and executive leadership teams must sync their knowledge and understanding of AIOps tools and technology, or risk falling behind their competition.

Akhilesh Tripathi is CEO at Digitate

Hot Topics

The Latest

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

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 ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

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 ...