The term AI is thrown around quite frequently in various tech communities. And it is for a very good reason. According to BMC Software, the cost of manually handling a service desk ticket is around $22. But with automation, almost 22% of these tickets can be resolved at no cost. Thanks to this disruptive and innovative concept, the picture of service desk management will go through drastic improvements.
Research by Gartner shows that by 70% of white-collar workers will interact with some form of chatbot by 2022.
A variety of strategies and technologies branch out from the term “intelligent automation”. Some of the terms that come under this umbrella include rapid-automation technologies (i.e., robotic process automation [RPA] software or scripting), artificial intelligence (AI) approaches such as deep learning, machine learning, natural language processing, speech recognition & synthesis, machine vision, and machine reasoning.
Managing service desks using AI-driven features like chatbots and self-service
We have been using self-service in its most basic form as a knowledge base, but the sophistication has just begun. With chatbots and AI-powered search recommendations, arriving at the right solution is much faster and easier. Using powerful AI features like predictive analysis, IT teams can better manage incidents and resolve tickets effectively and more efficiently.
Here are three key areas where AI can be leveraged to get maximum value addition for your business.
- Chatbots
- knowledge management
- incident/request auto-routing.
Some of the most basic chatbots run on NLP [natural language processing] that allows for conversation.
This can be used to carry out a targeted search of the knowledge base or answer faq-type queries. This capability of improved AI-powered search can also be extended to take further actions based on user inputs using RPA technology. Simple tasks like simple password resets and the creation of VMs in the private or public cloud can be just as easily automated. Using the auto-resolution feature, IT teams can speed up various processes and tasks by removing the manual overhead associated with high-volume and low-value service desk activities.
It could be tedious for a help desk agent to route incidents and request tickets to a proper support group. However, using AI it is possible to automate auto-classifying, prioritizing, and routing incidents or service requests to appropriate support groups.
AI-assisted knowledge management is proving to be a new step toward smart service desk management. AI-powered knowledge management includes an intelligent search function that goes beyond a set of specific keywords and understands the context and meaning. This means that search results are more relevant.
Auto Responding – The New Way Forward
Imagine this, users can now receive most likely solutions which are generated by auto-responders that are powered by AI. The AI managing the knowledge base can also keep track of previous interactions and other behavioural patterns. Using that data, it can make relevant suggestions regarding actions to be performed based, on managing incidents, changes, problems, and known errors. When the AI has enough data, it can even perform self-healing activities using all the data on previous engagements.
Like any other technical vertical, support-level responsibilities are evolving as well. Here’s what the spectrum of support levels looks like according to Gartner:
This proves that AI plays a central role in service desk automation to enable vital activities like self-service, self-diagnostics, and self-healing.
A study by Gartner shows that 75% of issues on average (service requests, common software issues, password resets, “how to” questions, and outage notifications) have the potential to be resolved without requiring Level 1 or higher support (i.e., “Level 0 solvable”)
This massive shift in paradigm enables current support staff to do more complex operations at L3 levels by freeing them from performing low-level, mundane tasks.
It is safe to conclude that AI can help reduce overall operating costs, improve user experience, increase agent productivity, help forecast IT issues, identify problems, manage changes better, and improve key metrics including resolution times and SLA compliance level.
About the Author:
Prashant Deshpande
Executive Vice President
Prashant heads global delivery of Vyom Labs consisting of various practice units such as BMC and ServiceRize. Prashant has illustrious career over thirty years in information technology and has served at senior executive levels with global companies such as: IBM, BMC, Veritas and Citibank.
Prashant has built, scaled and managed various IT, professional services & product development/support organizations.
His technical expertise is in IT infrastructure management, automation and managed services. He is passionate about business transformation using cognitive technologies such as AI and machine learning.