With newer advances in AI and Machine Learning, bots are dominating the customer service operation. AI promises to be one of the most disruptive and innovative technologies. Based on the 2019 Gartner CIO Survey, 14% of organizations employ AI and nearly 50% intend to do so in 2020. The face of the traditional service desk is changing rapidly with advances in AI.
According to Gartner, by 2020, 25% of customer service and support operations will integrate virtual customer assistant technology across engagement channels, up from less than 2% in 2015.
Bots can cut costs, reduce human errors, work continuously without taking any breaks. There is absolutely no doubt that bots can bring a great deal of efficiency in customer service.
The key question is can bots replace human agents?
Many times, customer service desks are treated as cost centers and human agents are replaced by bots. This may turn out to be a critical mistake as you are sacrificing customer experience. Losing a customer is more costly than the short term approach of eliminating human agents entirely to save costs. As it turns out, the most significant gains from virtual bots are from improvements in customer experience, not simply cost savings.
There are many cases chatbots are not suitable for customer interactions.
As you know, many times we get frustrated with older IVR systems (especially with the ones where there is no option to reach a live agent) and we literally pray to get human agent online. If all inputs from the customer are not fully anticipated, a poorly designed chatbot without proper training, can keep on asking more questions will frustrate the end-user. Human agents can show empathy to customers and calm them down in these situations where chatbots fall short. Also, chatbots cannot be an answer to users with physical disabilities like visual impairment.
For complex interactions, where there are too many questions to be asked, customers can get frustrated going back and forth. In this case, the catalog based forms is a better option to design. For example, creating an AD account where many inputs are needed.
Many times, bots taking full control in remediating a situation (such as rebooting a server in a given complex scenario where multiple steps are involved) is not advisable because various alternative actions could be possible based on the step executed. It becomes important to handle such tasks manually by human agents.
Basically, bots and human agents working in harmony in a hybrid model is the best of both worlds. Humans and bots possess different skills. Human customer service agents easily recognize when someone is frustrated and provide a response with empathy. AI-powered virtual agents, on the other hand, lacking emotional intelligence are programmed and trained to handle certain queries from the end-users and provide instant answers.
Bots can handle most of the basic queries coming from customers (such as, what is my leave balance, how do I set my printer etc.). The complex questions could be diverted to the human agents. The cumbersome navigation of service desk catalogues could be avoided by smarter bots. Chatbots are easy to program where a standard set of questions are expected from the users such as: booking a conference room.
Bots can perform all mundane tasks such as password resets, share folder access etc. which are laborious and not interesting to human agents. With a shift-left support model, basic tasks could be pushed to bots freeing the human agents to perform more value-added assignments. On the flip side, human agents can continuously train bots to become smarter based on interactions with customers.
Many of the complex SOP’s can be programmed using machine learning and alternatives could be given by bots to human agents to perform these step-wise actions without going through operational manuals. Bots can provide health-check reports to human agents to derive useful insights into the operations and provide further suggestions to take actions such as restarting a process, lowering the priority of a job consuming high CPU usage. The newly trained agents can really get benefitted with this tech-assisted bot model especially when L1 agents do not have the privilege to perform advance tasks.
All of these above cases show that AI-driven customer service cannot replace human agents to cut costs. The technology can help in making human agents smarter. On the other hand, human agents can fill the gaps in service where bots fall short.
When the customer wait time is significantly reduced by interactive bots, the customer is happy. The human agents are happy as they can focus on delivering higher value, complex tasks. The result is a significant improvement in overall customer service.
Our experience has been we can automate over 60-80% tasks by bots freeing human agents. The rest of the advanced tasks could be taken care of human engineers, especially in data center management. We also have our own AI based methodology to analyze existing ticket data to identify automatable candidates out of this data.
We offer an innovative service called “ServiceRize” which is a creative combination of bots and human agents. The human agents could be an extension of your service desk.
The overall result is enhanced customer experience, reduction in turnaround time while keeping the costs low.
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.
