It should not come as a surprise that the pandemic has impacted all aspects of the workplace, including the service desk. But behind the data, the full story of the deterioration of most of the IT Support metrics shows that Service Desk transformation can no longer wait. 

We asked Senior Executives to share their perspective on the evolution of end-user support and the Digital Transformation of the Service Desk. Today’s insights are from Rob Gwatkin, Global Senior Service Delivery Manager, in the Digital Service Management team at Veolia.

In previous blogs, I discussed the benefits of Natural Language Processing. Another field of interest is machine learning (ML). Machine learning (ML) holds significant promise for IT service management, for instance for incident categorization and routing. In this blog, I want to demystify machine learning and get your service desk team in the comfort zone. I will discuss about three use cases in IT Service Desk where Machine Learning generates tangible business benefits for customers.

You have invested time and money in the Atlassian Jira Service Management platform. You want to unlock more value, increase employee productivity and relieve your agents from recurring simple tasks. Here are 4 reasons Konverso’s Intelligent Virtual Agent brings more value to your Jira Service Management, with a user-centric and easy-to-use solution for Service Desk automation.

Veolia UK & Ireland started working with Konverso in February 2020. In the first weeks of the Covid-19 pandemic, Veolia decided to automate its IT Help Desk, to provide greater IT support to the teams transitioning from the office to work-from-home. Since June, Konverso’s Intelligent Virtual Agent has been live on Veolia UK & Ireland’s ITSM based on ServiceNow.

Knowing how an AI understands languages is useful to build your own Intelligent Virtual Agent (IVA) or select an “off the shelf” conversational AI platform. Yes we mean Intelligent Virtual Agent and not chatbot, because Natural Language Processing skills put Virtual Agents in another league. So here are the main technical elements that enable an AI to understand a variety of written and spoken languages.

Machine Learning is a vast field and its importance has grown significantly over the last few years. It now plays a key role in the performance of Virtual Agents. However, people are still confused about the relation between Artificial Intelligence, Machine Learning and Deep Learning. Going back to a clear definition is a sure start. 

On paper, bots, chatbots and intelligent virtual agents might seem quite comparable… until you start communicating with them. Because mastering the human art of conversation requires a very particular set of skills. 

You may have already read a lot of studies and white papers about bots, chatbots and intelligent virtual agents. Confusing, right ? Because unless you have directly been involved in a conversational AI project, the difference between those technologies might not be clear. So to give you the fundamental principles, here are 4 main characteristics of an Intelligent Virtual Agent (or IVA).

Intelligent Virtual Agents are conversational bots powered by Artificial Intelligence, capable of assisting humans in a variety of tasks thanks to an easy-to-use interface, from the IT helpdesk to HR and Finance. But what exactly are Intelligent Virtual Agents capable of, and what could you do with a Virtual Agent in your own organisation?