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The Benefits of Deploying AI in IT Operations

Akhilesh Tripathi
Digitate

Digital transformation reaches into every aspect of our work and personal lives, to the point that there is an automatic expectation of 24/7, anywhere availability regarding any organization with an online presence. This is a boon to consumers but a huge strain on the IT professionals who must meet that expectation in a rapidly changing environment. As much as 30% of the typical IT environment changes from year to year, forcing IT teams to reskill and stay on their toes in the midst of already-demanding jobs. This environment is ripe for artificial intelligence, so it's no surprise that IT Operations has been an early and robust adopter of AI.

Image removed.

IT's Redundant Task Problem

Hundreds of thousands of incidents can occur in mere minutes in today's complex, dynamic environments, generating overwhelming amounts of operations data. IT workers have to cut through this deluge to find and address problems like a credit card transaction mistakenly declined or a network crash that throws a crucial system offline. It's become nearly impossible for even the best IT teams to respond quickly and effectively.

Though these issues must be resolved, this reactive IT mode does not help the business grow. Worse, an IT worker can start to feel like the mythical Sisyphus, pushing a stone up the hill to solve one problem, only to see it roll down again when another ticket opens. Such an environment can drive even the brightest, most capable IT professionals to burn out and leave.

IT teams carry the triple burden of trying to prevent unexpected downtime — and the financial loss it entails — while improving IT efficiency and continually transforming customer experience. Doing so requires that IT workers engage in log analysis, performance optimizing, capacity planning and infrastructure scaling. While IT infrastructure is dynamic, its problems are well defined. These tasks demand finding patterns in massive data sets and are often dull and repetitive. They are perfect, then, for AI automation. AI tools can enhance both the speed and accuracy of such work, reducing stress on IT employees.

Improving Efficiency and Performance

The use of automation in IT is not new, but it typically has not scaled well in dynamic enterprise environments. Today's AI-based automation is different. IT departments using off-the-shelf AI tools are already reducing unscheduled downtime of revenue-generating systems. In fact, AI tools are helping IT operations resolve problems within minutes instead of hours and transforming customer experience for IT and the business overall.

AI can use multiple kinds of intelligence, making it autonomous, adaptive and scalable. As a recognition intelligence, it can find patterns in immense quantities of data. As a reasoning intelligence, it can tell what those patterns mean: Are they reflecting deviations in normal enterprise systems behavior that mean a system breakdown is looming or an attack from malicious sources is imminent? And as an operating intelligence, it can help manage the problem — both making recommendations for how to fix it and invoking automated, prescribed actions to fix it.

The IT environment features distinct towers of expertise. There's the database, middleware, operating systems, storage, network and so on. Each tower is staffed by people who know its area intimately but may have a limited view across the overall enterprise. AI improves how IT people see the connection between technology and the business. It can be a contextual engine that cuts across all of IT's siloed towers; it is better able to pinpoint the source of a problem than any individual in the organization. Experience shows us that the most difficult part of fixing IT issues is identifying the source of the problem.

Deploying AI in IT

AI's prominence in popular culture has created a variety of perceptions about what it can do, from panacea to paranoia. It is crucial for CIOs to have a clear sense of how and why AI is going to be applied in IT. CIOs who do not carefully define how AI will be applied risk losing control of business expectations for the technology.

CIOs can introduce AI into the IT department in a variety of ways. The greatest ROI comes from using it for business assurance, keeping revenue-generating systems running and fixing whatever problems do occur more quickly. Another effective way to get buy-in for and payoff from AI is to apply it to specific issues such as improving customer experience issues or driving IT agility.

Another benefit of AI for the IT team is that it may not be necessary to upskill current staff or hire new, hard-to-find AI talent. It doesn't hurt to have IT staff with AI skills, but vendors are building intelligence into their systems, and IT-oriented AI-as-a-Service offerings are available. From an enterprise perspective, AI-based IT should mean significantly less time putting out IT fires. That means CIOs can begin to redeploy their human capital, focusing their team more on the growth and transformation of the enterprise instead of keeping the lights on. Ultimately, that means AI will help the CIO be much more aligned with business needs.

AI offers immediate benefits to the IT department that will expand over time. It will continue to learn and be able to manage more complex tasks and issues. This will continue to free IT staff to better respond to customer needs and initiatives that drive business goals.

Akhilesh Tripathi is CEO at Digitate

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The Benefits of Deploying AI in IT Operations

Akhilesh Tripathi
Digitate

Digital transformation reaches into every aspect of our work and personal lives, to the point that there is an automatic expectation of 24/7, anywhere availability regarding any organization with an online presence. This is a boon to consumers but a huge strain on the IT professionals who must meet that expectation in a rapidly changing environment. As much as 30% of the typical IT environment changes from year to year, forcing IT teams to reskill and stay on their toes in the midst of already-demanding jobs. This environment is ripe for artificial intelligence, so it's no surprise that IT Operations has been an early and robust adopter of AI.

Image removed.

IT's Redundant Task Problem

Hundreds of thousands of incidents can occur in mere minutes in today's complex, dynamic environments, generating overwhelming amounts of operations data. IT workers have to cut through this deluge to find and address problems like a credit card transaction mistakenly declined or a network crash that throws a crucial system offline. It's become nearly impossible for even the best IT teams to respond quickly and effectively.

Though these issues must be resolved, this reactive IT mode does not help the business grow. Worse, an IT worker can start to feel like the mythical Sisyphus, pushing a stone up the hill to solve one problem, only to see it roll down again when another ticket opens. Such an environment can drive even the brightest, most capable IT professionals to burn out and leave.

IT teams carry the triple burden of trying to prevent unexpected downtime — and the financial loss it entails — while improving IT efficiency and continually transforming customer experience. Doing so requires that IT workers engage in log analysis, performance optimizing, capacity planning and infrastructure scaling. While IT infrastructure is dynamic, its problems are well defined. These tasks demand finding patterns in massive data sets and are often dull and repetitive. They are perfect, then, for AI automation. AI tools can enhance both the speed and accuracy of such work, reducing stress on IT employees.

Improving Efficiency and Performance

The use of automation in IT is not new, but it typically has not scaled well in dynamic enterprise environments. Today's AI-based automation is different. IT departments using off-the-shelf AI tools are already reducing unscheduled downtime of revenue-generating systems. In fact, AI tools are helping IT operations resolve problems within minutes instead of hours and transforming customer experience for IT and the business overall.

AI can use multiple kinds of intelligence, making it autonomous, adaptive and scalable. As a recognition intelligence, it can find patterns in immense quantities of data. As a reasoning intelligence, it can tell what those patterns mean: Are they reflecting deviations in normal enterprise systems behavior that mean a system breakdown is looming or an attack from malicious sources is imminent? And as an operating intelligence, it can help manage the problem — both making recommendations for how to fix it and invoking automated, prescribed actions to fix it.

The IT environment features distinct towers of expertise. There's the database, middleware, operating systems, storage, network and so on. Each tower is staffed by people who know its area intimately but may have a limited view across the overall enterprise. AI improves how IT people see the connection between technology and the business. It can be a contextual engine that cuts across all of IT's siloed towers; it is better able to pinpoint the source of a problem than any individual in the organization. Experience shows us that the most difficult part of fixing IT issues is identifying the source of the problem.

Deploying AI in IT

AI's prominence in popular culture has created a variety of perceptions about what it can do, from panacea to paranoia. It is crucial for CIOs to have a clear sense of how and why AI is going to be applied in IT. CIOs who do not carefully define how AI will be applied risk losing control of business expectations for the technology.

CIOs can introduce AI into the IT department in a variety of ways. The greatest ROI comes from using it for business assurance, keeping revenue-generating systems running and fixing whatever problems do occur more quickly. Another effective way to get buy-in for and payoff from AI is to apply it to specific issues such as improving customer experience issues or driving IT agility.

Another benefit of AI for the IT team is that it may not be necessary to upskill current staff or hire new, hard-to-find AI talent. It doesn't hurt to have IT staff with AI skills, but vendors are building intelligence into their systems, and IT-oriented AI-as-a-Service offerings are available. From an enterprise perspective, AI-based IT should mean significantly less time putting out IT fires. That means CIOs can begin to redeploy their human capital, focusing their team more on the growth and transformation of the enterprise instead of keeping the lights on. Ultimately, that means AI will help the CIO be much more aligned with business needs.

AI offers immediate benefits to the IT department that will expand over time. It will continue to learn and be able to manage more complex tasks and issues. This will continue to free IT staff to better respond to customer needs and initiatives that drive business goals.

Akhilesh Tripathi is CEO at Digitate

Hot Topics

The Latest

E-commerce is set to skyrocket with a 9% rise over the next few years ... To thrive in this competitive environment, retailers must identify digital resilience as their top priority. In a world where savvy shoppers expect 24/7 access to online deals and experiences, any unexpected downtime to digital services can lead to significant financial losses, damage to brand reputation, abandoned carts with designer shoes, and additional issues ...

Efficiency is a highly-desirable objective in business ... We're seeing this scenario play out in enterprises around the world as they continue to struggle with infrastructures and remote work models with an eye toward operational efficiencies. In contrast to that goal, a recent Broadcom survey of global IT and network professionals found widespread adoption of these strategies is making the network more complex and hampering observability, leading to uptime, performance and security issues. Let's look more closely at these challenges ...

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The 2025 Catchpoint SRE Report dives into the forces transforming the SRE landscape, exploring both the challenges and opportunities ahead. Let's break down the key findings and what they mean for SRE professionals and the businesses relying on them ...

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The pressure on IT teams has never been greater. As data environments grow increasingly complex, resource shortages are emerging as a major obstacle for IT leaders striving to meet the demands of modern infrastructure management ... According to DataStrike's newly released 2025 Data Infrastructure Survey Report, more than half (54%) of IT leaders cite resource limitations as a top challenge, highlighting a growing trend toward outsourcing as a solution ...

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Gartner revealed its top strategic predictions for 2025 and beyond. Gartner's top predictions explore how generative AI (GenAI) is affecting areas where most would assume only humans can have lasting impact ...

The adoption of artificial intelligence (AI) is accelerating across the telecoms industry, with 88% of fixed broadband service providers now investigating or trialing AI automation to enhance their fixed broadband services, according to new research from Incognito Software Systems and Omdia ...

 

AWS is a cloud-based computing platform known for its reliability, scalability, and flexibility. However, as helpful as its comprehensive infrastructure is, disparate elements and numerous siloed components make it difficult for admins to visualize the cloud performance in detail. It requires meticulous monitoring techniques and deep visibility to understand cloud performance and analyze operational efficiency in detail to ensure seamless cloud operations ...

Imagine a future where software, once a complex obstacle, becomes a natural extension of daily workflow — an intuitive, seamless experience that maximizes productivity and efficiency. This future is no longer a distant vision but a reality being crafted by the transformative power of Artificial Intelligence ...

Enterprise data sprawl already challenges companies' ability to protect and back up their data. Much of this information is never fully secured, leaving organizations vulnerable. Now, as GenAI platforms emerge as yet another environment where enterprise data is consumed, transformed, and created, this fragmentation is set to intensify ...

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