In the past few decades, organizations have become more competitive through the sub-contracting of Help Desk functions. However, for developing efficiency all over the enterprise, the productivity of internal human resources must also rise.
One of the areas where Artificial Intelligence (AI) is required is help-desk. Due to upgrades in deep learning, natural language understanding, and infinite computing, the application of AI in organizations has become more practical than ever. IT help desk has become a significant part of today’s business functions. It helps enterprises to offer continuous technical support to their various stakeholders like customers, suppliers, employees, etc. It ensures timely and prompt support, rescuing the agents from running into basic technology complications impacting their efficiency. The establishment of Chatbots in the IT service desk system helps an organization to change its support productivity.
A chatbot is an Artificial Intelligence application that interfaces with users using a conversational program. Machine Learning and Natural Language Processing are the two languages that are used in developing a chatbot. AI chatbots are self-learning software systems that interpret the human language without the need for human help. Nowadays, various companies are looking for AI help desk software as it can answer promptly to the agent’s support queries and resolve them immediately, in most cases. It can increase the efficiency of the end-users as well as allow the IT help desk team to concentrate on complicated queries and other digital modifications efforts.
The three essentials of an AI bot for your enterprise IT Help Desk are:
- Enterprise Language Understanding using both sparse and dense data
Traditionally, IT Help Desk professionals are trained on how to handle service requests promptly. In the same way, AI chatbots must be trained to understand language related to the organization. AI bots must use an ‘enterprise resemble model’ which stimulates the knowledge base related to your organization.
An ELM defines the language as a colloquialism, cryptic notations, acronyms, technical jargon, and domain-specific vocabulary and intents that are expressed mostly in IT Service Desk requests. Therefore, the first step to understand conversations specific to any enterprise application of AI is to have an ELM.
Sparse Data v/s Dense Data
Sparse data means a low volume of data that can be interpreted by using a spreadsheet. Whereas; dense data means a large volume of data. An AI bot helps to analyze high volume queries and surface intentions automatically from the data sets to create ELM.
- Interactions with users through an independent AI Worker or dialogue with an AI assistant
Once we have built a comprehensive ELM, we must decide how our AI bot should communicate within our organization’s IT Help Desk environment. AI bots can function as an AI assistant or worker.
AI Worker v/s AI Assistant
An AI Worker does not involve continuous interactions with end-users. In fact, it is invisible to the end-users as the chatbot is installed directly on the IT Service Desk software, which captures incidents. AI Workers are either trained to resolve service requests or, they are deployed to do some pre-processing to help a help-desk agent in resolving the ticket. The AI Worker can only resolve the ticket if it is trained to do so. Otherwise, it will put the service request back in the queue for the help-desk agent to take action.
For example, The AI Worker will automatically execute the commands, such as – “Increase disk space,” “Unlock my account,” or “Reset password” on the back-end if a human agent requests the chatbot to do so.
- Ability to fulfill back-office requests using FAQ knowledge bases, RPAs, or APIs
The two methods to create the workflows for AI Workers to accomplish back-office requests:
- Use Robotic Process Automation (RPAs) and APIs
- Use an FAQ Knowledge Base
FAQ Knowledge Base v/s RPA/API
The ELM alone will not serve unless an AI Bot will completely understand a service request. Most IT Help Desk tickets involve extracting many complex service requests from the ticket and forwarding them to RPA/APIs to do a back-end function.
If there is a service request related to the FAQ knowledge base, for example- “I need to exchange my phone.” An AI chatbot would collect the intention “exchange phone” and provide the appropriate support link from the organization’s knowledge base. This helps to fulfill monotonous IT help desk requests without disturbing higher-level support engineers, which in turn creates effective workflows.
Conclusion
AI-powered bots and cognitive automation helps enterprises to remove their IT bottlenecks and resolve mundane issues easily. They are swiftly becoming the chief reason behind the digital transformation all over the organizations. It helps in automating the IT service-desk function, lowering the burden on IT staff. This is the perfect time to welcome this technology and use AI chatbots for IT Service Desk automation.