IT service management (ITSM) is at a crossroads. In recent years, IT teams have drastically changed how they communicate and collaborate. The evolution of IT infrastructure with the advent of cloud computing and big data has led to larger fleets of servers, more storage systems, and more complicated networks. This has led to more than just an increase in the quantity of devices and services we need to manage—there’s been a qualitative change in the level of complexity of the systems we need to manage.

Because ITSM technically encompasses everything from service request management, lifecycle management, incident management, and problem solving to change management and asset tracking, supporting users efficiently is more challenging than ever; and, as more than 54,000 technology roles sit unfilled, this herculean task is often falling to a skeleton crew. 

That may be where we as an industry are today—but it’s not where we have to remain. Embracing new technologies and tools may have made our digital landscape more complicated than ever, but as technological challenges have evolved, so have solutions. One of the most compelling examples of this is the incorporation of transformative artificial intelligence (AI) and machine learning (ML) capabilities. 

Innovative enterprises are finding ways to put AI to work in the places where it can provide the highest lift and have the strongest impact on customers. For instance, by incorporating AI into ITSM functions—to simplify help desk ticketing, IT asset management, and end-user support—companies are better able to eliminate barriers to employee support services, and conserve time, money, and resources while improving customer satisfaction. 

AI is already changing how things have always been done, from machine learning handling big data in a way that humans simply cannot, to automations taking over a large amount of manual service desk processes. AIOps are providing ways to streamline workloads and processes; machine learning tools are removing bottlenecks and compatibility issues from migrations to the cloud. All these efforts are aimed at freeing up human IT capital to further service management and agile development efforts across organizations. Customer and internal employee service powered by artificial intelligence is quickly becoming the standard for many organizations. 

There is a world of opportunity for artificial intelligence-powered automation in both proactive and reactive service delivery. 

Think about it like driving in the carpool lane—with AI as your co-pilot, you can accelerate in a lane with fewer limitations and less competition. Ultimately, incorporating AI into ITSM doesn’t just help you reach your goals faster; it helps you reach them more efficiently, and without getting burnt out or breaking down in the meantime. Preventative maintenance should be a policy to live by—whether before a road trip, or when maintaining your business-critical systems. 

When incorporating AI into your services and strategies, here are some ways you can leverage the power of automation and smart technologies to drive your operations into high gear: 


With automated improvements to service delivery, consider how automation and AI can further your visions of enterprise service management to support beyond IT initiatives and unify departments across the organization. (For instance, by eliminating silos with streamlined processes and routing rules, connecting cross-functional internal service providers, and building the case for enterprise service management.) 

You can also consider optimizing service management operations to automate data collection or suggest knowledge content to drive efficiencies and self-service. This can lead to, for instance: shorter response times with AI-recommendations linked to potential workarounds or resolutions, based on historical trends and insights.

Finally, you can even experiment with combinations of tools that work best for your organization’s needs—for instance, bringing ITSM together in a unified way with Observability is a perfect recipe for companies undergoing rapid growth, digital transformation, or difficulties preventing system failure. 


We want our lives to be easier. We want to be able to increase efficiency and focus on core tasks. But at the same time, we don’t want to diminish the human element of service. AI-powered automation isn’t here to steal jobs, it’s here to free up workers by eliminating human intervention, enabling them to focus on tasks that require human interaction. Beyond streamlining operations, this degree of automation impacts the user experience, fueling more positive service engagements. We already see it today, enhancing our overall user experience: on our personal computers and mobile devices with automated backups; on search engines providing recommendations; as well as automatic app and operating system updates. 


It should be noted that, when it comes to AI, you can’t just throw everything at the wall and see what eventually sticks. Balance is just as much a part of any solution as technology is. To succeed, especially when it comes to automation, you’ll need to somehow balance strategy, thoughtful planning, measured implementation, and scalability. 

When implementing any new technology or process, ensure these changes will work for your business and your people, but won’t become a disruption. It’s important to first “look under the hood” of your organization and take frank stock of what you’re doing well, what you could be doing better, and where your teams truly need the most support. Some areas of consideration should include the most frequent pain points customers experience, upcoming business growth priorities, and even potential cultural pushback from within the organization. 

Once you recognize the inherent benefits of these smart technologies, the next step is precisely planning how you want them to work for your business goals. Review where you are and ultimately where you want automation to take your service delivery by enhancing what works and improving what doesn’t. Remember, AI + automation should drive positive and impactful results—not create more work.

About the Author

Krishna Sai is responsible for the AIOps, service management, and database portfolios at SolarWinds. He is a seasoned leader and entrepreneur with over two decades of experience scaling global engineering teams and building winning products across multiple industries. Sai has held leadership roles at Atlassian, Groupon, and Polycom, co-founded two technology companies, and holds several patents.

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