Text classification with hierarchical taxonomies is a fundamental requirement in IT Service Management (ITSM) systems, where support tickets must be categorized into tree-structured taxonomies. We present a dual-embedding centroid-based classification framework that maintains separate semantic and lexical centroid representations per category, combining them through reciprocal rank fusion at inference time. The framework achieves performance competitive with Support Vector Machines (hierarchical F1: 0.731 vs 0.727) while providing interpretability through centroid representations. Evaluated on 8,968 ITSM tickets across 123 categories, this method achieves 5.9 times faster training and up to 152 times faster incremental updates. With 8.6-8.8 times speedup across batch sizes (100-1000 samples) when excluding embedding computation. These results make the method suitable for production ITSM environments prioritizing interpretability and operational efficiency.

There are several types of AI that can be used in ticket management system. One of the most common types is natural language processing (NLP). NLP allows AI-powered ticket management system to understand customer inquiries and respond appropriately. Another type of AI that can be used in ticket management system is machine learning (ML). ML allows ticket management system to learn from customer interactions and improve over time.

The latest technology partnership will support Morgan & Morgan's efforts to enhance IT services to its more than 3,700 distributed employees. An active user of ServiceNow's IT Service Management (ITSM) platform to manage daily IT requests, Morgan & Morgan required a ServiceNow-centric voice and call center solution to optimize the experiences for its employees while leveraging its existing on-premise environment. In addition, the organization was eager to apply Natural Language Processing (NLU), AI, and intelligent call workflows to solve for repetitive manual tasks to allow for a more efficient use of its IT Service Desk resources. "Our goal is always to provide an efficient white glove service for our Attorneys and staff so they can continue to provide the same efficient white glove service to our clients. To do this, we needed to find a voice solution that integrated with our instance of ServiceNow as seamlessly as possible to be an extension of the Service Desk team while empowering our end users", explains Ismael Tanon, IT Manager at Morgan & Morgan.

All the sessions from Transform 2021 are available on-demand now. Nearly all IT managers (93%) are currently exploring or deploying some level of AI to streamline help desk systems, according to a new report from Freshworks. Half of IT managers said they have already implemented AI tools. Nearly 70% of IT managers said AI is either critical or very important for upgrading and modernizing their service desk capabilities. Even so, respondents said there are certain prerequisites for AI-enabled solutions.

ServiceNow Inc. is beefing up its artificial intelligence development capabilities with the acquisition today of a company called Element AI Inc. that's widely known as one of the pioneers in the field. Montreal-based Element AI launched back in 2016 as a professional services firm focused on helping traditional enterprises implement machine learning. The startup garnered significant industry attention from the outset thanks in part to its high-profile co-founder, the well-known deep learning researcher Yoshua Bengio, who won the Turing Award in 2018 for his contributions to the field. Element AI has gradually expanded its focus since its launch by creating a fund to support fellow machine learning companies and introducing ready-made AI tools. The company's offerings include Knowledge Scout, a search engine for manufacturers that speeds up the diagnosis and repair of production line issues by giving technicians relevant information about previous incidents with similar characteristics.

As digital transformation gains momentum, CIOs are under increasing pressure to choose AI-native ITSM projects that return quick value in increased employee productivity, cost savings, bottom-line operational gains, and customer satisfaction. But this is a tall order. So CIOs need to look for projects that show clear results and demonstrate the wisdom of investing in new technology--the sooner the better. AI is revolutionary and visible, and that means the stakes are high when it comes to implementing a project. It's natural for a CIO to want to move cautiously, as Gartner notes, "Nearly two of three organizations cited finding a starting point as a concern."

Artificial intelligence and machine learning can help make ITSM processes more efficient. CIOs are now using artificial intelligence (AI) and machine learning (ML) technologies to make IT service management processes more efficient. A typical use case for artificial intelligence in ITSM involves natural language processing (NLP). User requests for IT services are automated using NLP. IT practitioners get a deeper understanding of their processes by applying machine learning (ML) to ITSM data.

"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.

A logo of IBM (International Business Machines Corporation) sits on their offices at Yeouido, the ... [ ] financial district on October 13, 2020 in Seoul, South Korea. Every day, there is a batch of AI announcements that are sent out--and many of them are mostly fluff. But of course, some are worth paying attention to. For example, consider one from IBM and ServiceNow, which have announced an expansion of a strategic relationship. For the most part, it is focused on what matters--that is, driving measurable results that scale across organizations.

IBM and ServiceNow have expanded their strategic partnership to combine IBM's hybrid cloud software and professional services to ServiceNow's intelligent workflow capabilities and IT service and operations management products. The solution is engineered to help clients realise deeper, AI-driven insights from their data, create a baseline of a typical IT environment, and take succinct recommended actions on outlying behavior to help prevent and fix IT issues at scale. Together, IBM and ServiceNow can help companies free up valuable time and IT resources from maintenance activities, to focus on driving the transformation projects necessary to support the digital demands of their businesses. "AI is one of the biggest forces driving change in the IT industry to the extent that every company is swiftly becoming an AI company," said Arvind Krishna, Chief Executive Officer, IBM. "By partnering with ServiceNow and their market leading Now Platform, clients will be able to use AI to quickly mitigate unforeseen IT incident costs. Watson AIOps with ServiceNow's Now Platform is a powerful new way for clients to use automation to transform their IT operations."