Service desk managers have been discussing Artificial Intelligence for several years. However, companies are now trying to figure out where and how they should invest. This is because they can choose from a variety of paths depending on the service desk strategy they are using.
Management of service desk tickets is a major challenge for companies. According to the HDI Technical and Salary Report 2017, 55% of support organizations saw an increase in ticket volume, rising to 61% for 2018. Gartner stated that scaling support has been a problem for most organizations Without increasing manpower to meet end-user demand for support channels.
How can AI Help with These Problems?
You can identify areas where AI can be beneficial to your service desk. This will give you a quick win with measurable ROI. It’s not easy, but there is still hope. YIf you implement simple solutions, self-service engagement is a great way to quickly see high returns on your investment. in this blog, we discuss artificial intelligence technologies that can transform the way your service desk works.
1. Chatbots and virtual agents
Chatbots and virtual agents should not be surprising that they are at the top of our list. Live chat has been used by organizations for years as part of their self-service strategy to increase customer engagement. Traditional chat is only possible if a person has to communicate with the other party.
Chatbots and virtual assistants can be used as gatekeepers to help “auto-triage” simple requests. This allows your service desk staff members to concentrate on more complex requests that really require human support. Chatbots and virtual agents can automate access to FAQs, knowledge, and service requests, allowing customers and employees to have non-human interactions that feel human.
You can calculate the return on investment by making deflected calls through the service desk
- Chat-based self-help tools perform well
- The number of pre-qualified, automated tier-1 troubleshooting request
- The availability of more technicians has led to greater progress in high-value projects.
Our list continues to cover key features that make chatbots and virtual assistants more effective, increasing your chances for a successful AI project.
2. Natural Language Processing – NLP
Natural Language Processing (or NLP) is an important foundational tool in your future AI project. NLP, a subfield in computer science and artificial intelligence that focuses on the interaction of humans and computers’ language, is used for context.
NLP’s most important feature is its ability to help AI interfaces like chatbots or virtual assistants better understand human language, allowing them to communicate with people more effectively and accurately. Let’s take, for example, the case where you order an 8-inch Amazon Fire tablet with your voice assistant. Your assistant may not be able to recognize your request without NLP and could even end up saying something completely wrong, such as “setting an 8-inch surface of the Amazon forest on Fire!”
You need to make sure that your customers feel comfortable using these technologies when you want to increase user engagement with self-service or self-help platforms. This starts with the technology being able to understand what the end-user wants in their native language and giving accurate answers.
Automation is the best way to provide accurate and efficient service Chatbots should provide automated solutions and answers that are specific to the user and their environment. The bot should understand the user’s context, including their role within the company, their direct manager, access and management of devices, their approval level, and any other relevant information. This is crucial to provide a useful and efficient user experience.
End-users may have frustrating experiences such as selecting a device from a long list or choosing scenarios from a knowledge base that have different journeys depending upon the building they work in. This could lead to a call to the support desk. It’s easy to see it like this: When you call customer support, you expect a human representative to verify your identity, including your account information. A bot will not be able to meet your expectations. You could argue that a bot should have a much easier time querying for the information than a human searching your CRM.
4. Automating Cross-Platform Actions
Talking about querying CRM data – giving your end-users the ability to “take action” across enterprise platforms directly from a chatbot/virtual assistant will close the loop for value-add artificial Intelligence.
End users expect to get answers to their questions when they interact with bots. They don’t want to go to a portal, 3 third applications, or other applications to find the answer to their questions or get service. Let’s return to our example of ordering an Amazon Fire 8-inch. The bot assumes you know who you are and helps you troubleshoot any issues that will help you to order a replacement tablet if your current tablet isn’t working.
Integration into your IT Service Management Platform could be a great value-add to self-service engagement. This interaction will be extremely easy for your end-user by having the chatbot submit an order for a new 8 inch Amazon Fire, Auto-route the ticket to a technician or team. Check against the stock and provide or procure the item, without having to toggle between applications or calling the service desk.
Artificial intelligence is not just about a chatbot. It can also help increase engagement with customers and employees. This journey requires many considerations. You should focus on quick wins with measurable ROI, comfortable conversation and context, valuable articles or FAQs, and the ability for the user to take immediate action on the solution or answer they receive.