December 22, 2017

The Future of the AI-Powered Service Desk

Written by
Chris McManus
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When you hear and read about artificial intelligence (AI), it always seems to concern massive, culture-changing ideas — self-driving cars, personal-assistant robots, and doomsday military scenarios dominate the headlines.

That world, while interesting (and/or terrifying) is a long way from our current reality. There are, however, many smaller-scale uses for “smart” technology on the immediate horizon.

Take your service desk, for example. Traditionally, it’s been reactive. User calls or emails in a request or opens a ticket. Technician sees it, gathers any additional information from the user, prioritizes it, routes it, and it is eventually addressed. Every so often, the organization can run a report to see how effectively its responding. There are a lot of administrative steps in that process, so it’s not exactly efficient.

AI, machine learning, and automation are changing that process, to everyone’s benefit.

ALSO READ: ITSM vs. Help Desk Software — What’s the Difference?

Incident and Service Request Creation

Sometimes your users need help, but they don’t know exactly how to categorize their issues. Heck, maybe they just aren’t technically savvy, but their issues are important and they know they need something. This confusion can create time-consuming processes for technicians who need to collect data, recategorize, and reroute these tickets and requests. Simple AI technology can suggest categories and subcategories to the user with just a basic amount of information about the request, which will dramatically improve the way that ticket or request is handled the rest of the way.

The self-service portal is another feature that has already eliminated some of this wasted time. Instead of an email or phone call to submit tickets or requests, users can visit the portal, where they can access a knowledge database to try to solve easy issues themselves. This is helpful on both ends. Techs aren’t dealing with as many simple issues (such as resetting passwords, or monitor connections), and users don’t have to wait for a response (especially outside of business hours) for an easy fix.

As AI capabilities evolve, imagine connecting a chatbot to a service management solution. Now your users can ask the chatbot a question through any device to access a knowledge database. Imagine a sales rep is driving two hours to an appointment, stops receiving emails, but can simply use voice command for the chatbot to explain the problem. Then the bot, with access to all of the related tickets and knowledge articles in the database, can suggest a solution or create a properly categorized ticket. These are all possibilities as we harness the power of AI and machine learning.

Predictive and Preventative

For a real-life example of the impact of AI-powered service desk, imagine all the schools and universities that recently welcomed thousands of students back to their campuses. Large, public universities might have a 30,000-user influx, 8,000 of which are brand new to the school. That’s a lot of incidents, requests, and overloaded networks in the making.

Planning ahead would be helpful, but how do you know just how much manpower will be needed? And how do you plan for users requests that haven’t happened yet?

Machine learning is the answer. It can pull the necessary data, and analyze it to help schools predict and prevent these issues. An AI-powered service desk solution could predict outages, suggest appropriate staffing for the influx, and automatically alert a massive amount of users to some potential issues their peers are seeing.

Organizational Impact

Some of these technologies are in early stages, so you may need to start with simple tasks. Chatbots, for instance, might be equipped for password resets in the near future, but it may not be a good idea to ask a bot to onboard a new employee.

It’s also important to remember that “smart” technologies cannot take the place or your organization’s people, processes, and best practices. Machine learning needs data to learn from. In this case of service management, the data is your everyday people and processes in your organization. When properly deployed, it can help automate service management responses. And it can make your technicians’ lives easier so they can focus on actual support instead of tedious administration. If you are in the market for ITSM software, check out our list of the best ITSM tools.

Chris McManus is a content specialist at Samanage. You can read more about IT service management and smart technology here, or sign up for a free Samanage trial to customize an environment for your organization.

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