In this relentless, highly competitive, and dynamic world, the necessity for speed has become an unsaid mandate in the lives of the people. Organizations all over the globe want to serve the customers with an ultimate experience, yet demand enhanced productivity with the limited use of resources, high savings on expenses, and improved efficiency. On the other hand, clients also expect an instant resolution to their problems, anytime anywhere.
Organizations face a lot of challenges to make this all work. These challenges could be overcome with the help of smart AI platforms. These platforms are designed and developed using smart concepts like Natural Language Understanding (NLU), Machine Learning (ML), and Robotic Process Automation (RPA).
Now, the question that comes to everyone’s mind is, will these unconventional platforms turn around the working of IT Service Desk and Customer Service and enhance their efficiency? Let’s find out.
Gartner forecasts that by the year 2022, about 40% of the total number of clients facing any kind of governmental or personal issue will be consulting an AI VSA (Virtual Support Agent) on a day-to-day basis for gaining any sort of information or for automation or business process support.
All these actions come under one of these 4 categories: robotic process automation, proactive notifications, intelligent knowledge, and predictive analytics.
For example, conventional AI can perform various tasks. It can correlate with the structured & unstructured datasets that are tangled with various systems; it can normalize and can crawl, simultaneously or all at once. It can likewise help companies to readily provide data access to its customers and employees.
Customers can easily gain such data by simply engaging themselves with a human-like AI agent operator. These kinds of agents are now easily powered by NLU methods to precisely extract the intent of the customers.
Alongside RPA, AI can help the organizations to rapidly, cost-effectively as well as efficiently work on all their processes and tasks. The customers as well as the employees are finally equipped with complete, enterprise-grade process automation and management solutions that smoothen out and self-serve the client’s everyday obstacles.
These obstacles vary from provisioning of an application (Outlook, Zoom, and so on.), network troubleshooting (VPN, Wi-Fi, etc.), approval workflow automation, password management, etc. The customers have to simply speak, text, or chat with the AI operator, who is comprehending all their intents in order to get a resolution to their problem.
Conversational AI assists with prescient examination or analytics too. For instance, manually approaching service demands devours a great amount of time that a help operator or agent could leverage for performing other significant assignments.
To date, IT & Customer Service Desks have robotized a massive number of requests of services by characterizing rules that categorize requirements depending on the preset parameters and conditions.
However, these guidelines are static—which means that they would not improve or adapt with time. By leveraging AI technology that includes Machine Learning, service desks would now effortlessly develop a classification model based on notable service desk data.
They can then ideally allocate service requirements by taking into account service specialists’ before performance, expertise, workload, availability, and anything that is relevant to the requirement.
The best part is that these ML models will turn out to be highly precise over time by taking into account the live data. Such ML-based models are boundlessly more effective than manual or rule-based automation.
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Lastly, Conversational AI can assist with proactive warnings as well! It can help the clients by notifying them about open service inquiries that may relate to their tasks, jobs, or locations, which then gets converted into a comprehensive and quick response to their requests.
For instance, suppose that a service inquiry was opened for toner substitution on a printer situated in a particular Enterprise. Conversational AI can either proactively advise all the employees in the enterprise building about the transitory disconnected status of the printer requiring toner substitution or can quickly advise all the users that are engaging themselves with virtual specialists that a service request was made for that issue.
Why is Conversational AI gaining popularity now?
For starters, we could say that the sheer scale, the infrastructure speed, and its availability has given rise to much bolder algorithms for dodging highly ambitious issues like Natural Language Generation (NLG) and Natural Language Understanding (NLU).
Not only is the tool faster, but it sometimes gets augmented by specific varieties of processors (e.g., TPUs), it is also available in the form of cloud services.
The thing that once ran only in specific and specialized labs with access to supercomputers would now be deployed to the cloud at a very minimal expense and substantially without any problem. The cheap storage capacity makes it possible to store all kinds of data which can come in handy in the future.
All these unique abilities have increased its popularity in providing flawless solutions that go beyond simple statistical data analysis to promise new insights and intelligence.
Due to the cheap storage and unprecedented infrastructure, the complex AI algorithms like Deep Learning (algorithms that emulate the human brain) have finally left their origin of academic lab environments and established an industry presence with a level of maturity that is well-understood and appreciated.
Subsequently, a significant part of the former operational protection from enterprise AI adoption is now long gone. There are endless other benefits of AI that effectively help the IT and other industries to work effortlessly. Every industry must therefore consider transforming their customer service in a magnificent way with AI.