Information Technology Service Management (ITSM) helps in monitoring, analyzing, and improving the quality of IT services to enhance customer satisfaction. On the other hand, Artificial Intelligence for IT Operations (AIOps) aims at providing self-learning and intelligent solutions to run IT systems smoothly by optimizing the resources available. But what if these two could work together? What if they could help each other out? Well, they can, and they do!

Buzz in the IT industry around AIOps has died down considerably over the last three years. Amid the waning fanfare, however, real-world use of IT automation based on machine learning algorithms has emerged among enterprises. AIOps -- or AI for IT Operations -- refers to the use of machine learning algorithms to automate routine IT tasks. That can include sifting through IT monitoring alerts, responding to incidents or handling the so-called "undifferentiated heavy lifting" required to do routine maintenance on infrastructure systems. The term emerged in the mainstream in 2018, and by 2019, AIOps had become a common industry buzzword, prompted several mergers and acquisitions among IT vendors and along with them, plenty of speculation about a highly automated, AI-driven future for computing.

"The end goal of good AI infrastructure is similar to traditional IT," said Ken Zamkow, general manager for North America at Run:AI, an AI virtualization tools provider. This includes enabling users in the organization, such as data scientists and engineers, to work faster and more efficiently while keeping costs in check and maintaining control, visibility and security. However, the underlying technologies are different because AI is based on long and repetitive experiments rather than pure coding; the data sets involved are significantly larger; and the compute needs are much greater and involve much more expensive hardware. "Getting all of this right is the key and the main challenge," Zamkow said. Part of the problem lies in navigating the huge variety of workflows, tools, frameworks and platforms that are available for AI training and deployment.

As technology grows and changes, it's no surprise that IT Service Management (ITSM) has done the same. And, while this may mean headaches in the short-term, it also creates nine important ITSM trends moving forward. At this point, agile development is more than a fad – it's here to stay. And, it will soon make its presence felt in ITSM through the latest generation of the Information Technology Infrastructure Library (ITIL). This widely recognized IT framework is the hottest conversation topic in today's ITSM world because of its potential to improve service management.

Digital transformation is sweeping across all aspects of business, and IT service management (ITSM) is no exception. Just as artificial intelligence (AI) brings disruptive change to other operations, it has begun to disrupt how ITSM is done. Service desk managers need to be aware of what AI actually is and what it has to offer. Though these two terms are often conflated, automation and AI aren't the same things. In fact, it's essential to understand how they are different. With automation, you're trying to offload technology tasks that are typically done manually and are repetitive and prone to error.