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.

Summer is in sight and vacations are on people's minds--but there's no such thing as an enterprise going on holiday. Businesses need to run 24/7, which is why leaders need to take a hard look at their digital processes and ask themselves: Where can technology really step up to make a positive impact while ensuring everything's running smoothly? When you digitize the enterprise, it's easy to get your wires crossed. I've noticed something curious while meeting with business executives recently at ServiceNow's InnovationPark, which is traveling around the country to immerse customers in real-life Now Platform experiences. Regardless of industry or the size of their enterprise, these executives were telling me very similar stories.

Organizations are leaning in hard to technologies like AI to facilitate faster, more productive operations. But in a recent meeting with a large company to discuss how AI can improve their customer and support experience, I was reminded there's more to the story than zeros and ones. AI works best when you put people in the center of your efforts. After my presentation, one of their AI experts started peppering me with questions on model recommendations for different situations in the customer support journey. Valid questions, all--but she was missing a crucial part of the conversation: people. I asked her, "What behavior are you trying to change?

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!

Your first thought likely goes to the doctors and nurses involved in an appointment or procedure. You might love your doctor. The last things healthcare practitioners want to spend time on are slow, disconnected, manual tasks. There is also a "before and after" to consider. To secure an appointment, you had to work with someone in scheduling.

When I started working as a mainframe operator in IT in 1988, I felt like I was part of a secret club. None of my family understood what I was doing; my friends would ask, "what's a mainframe and why do you have to work nights?" My onboarding took months, and a typical workday began with staring at a blank screen. Since mainframes didn't come with a mouse, I would enter memorized commands like " 3.4" and "Sys3.AF*" to navigate the data sets I needed to find. I don't think many workers today would put up with that.

Here's a fun game: Name one person you know who enjoys sitting on hold, waiting for a customer service agent to resolve an issue or answer a question. AI can transform your customer service experience--if you implement it with care. But what if I were to say that AI can enable a world where you'll never again be held hostage on hold, wincing every time the smooth jazz version of Duran Duran's "Hungry Like the Wolf" repeats ad nauseum? It's true--customer service and support is a prime candidate for using AI to improve the customer experience and enable the team to scale. As the person responsible for operationalizing AI within ServiceNow's customer support experience, I seek out stages in the customer journey where AI can automate processes.

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.

Did you miss a session at the Data Summit? Santa Clara, California headquartered ServiceNow, a provider of cloud-based solutions that define, structure, manage, and automate workflows for enterprise operations, today launched the latest version of its Now Platform, bringing an all-new RPA Hub and an improved visual experience. Officially dubbed Now Platform San Diego, the release brings new robotic process automation (RPA) capabilities to empower enterprises with the "true potential of hyperautomation" and help them create smarter, faster and better ways of working to drive productivity. It is generally available starting today. Today, organizations across sectors are moving to digital business models to thrive in the new normal and adapt to changing market conditions. However, more often than not, disconnected critical systems and dependence on specialty Centers of Excellence (CoEs) disrupt this shift, resulting in expensive, repetitive, and manual work of connecting the silos for employees.