In the past decade advances in Artificial intelligent technologies have helped it enter various industries as AI influenced assistants. But most of them like Siri and Google assistant have limited conversational skills. Through machine learning, the assistants could learn different responses to queries and hence would improve its functionality and accuracy.
Problems and implications:
Some of the problems with normal chat-boxes or human conversational agents are as follows:
Limited queries: Chat boxes are programmed to answer only a few specific questions based on the domain. A human conversational agent can at a time, answer only a few queries. These limits affect the efficiency of the company.
Customer satisfaction: Due to the limited queries solved by chat boxes, and the higher expectations of customers, they are seldom satisfied with the service. In terms of personal conversations, people expect a degree of emotions which such chat-boxes are unequipped to provide.
Limited languages: Most of the chat-boxes and human conversational agents find it hard to sense the language spoken by customers. Moreover, the translation feature of such chat-boxes isn’t efficient enough and takes more time as the length of the conversation increases.
Work-force: To hire a workforce efficient enough to handle all the queries, takes up a lot of the company resources which could have been used in other departments.
Companies like DheeYantra provide AI based cognitive conversational agents to solve the above problems in the following ways:
Improve productivity: Through in-built information and real-time updating of domain knowledge, AI-based conversational agents can improve the productivity of a company. For e.g. DheeYantra’s dhee.ai comes pre-trained on the domain knowledge and through further training in business product and servicing it would be well equipped to handle monotonous & repetitive queries, businesses Sales. Through these features, support & marketing executives will get to make use of their time more productively.
Cost optimization: Through the applications of AI in chat-boxes, the finance for handling human resources would decrease. Moreover, other than human assistants, they can also complete mundane monotonous tasks to improve the company’s efficiency.
Customer satisfaction: Through analyzing the history of conversations, the AI-based cognitive conversational agent can respond effectively to a customer’s query. This way the customer is both satisfied with the experience and the solution.
Analytics: The AI-based agents also provide analysis on the conversation between itself and the customer with other features such as languages to be supported, adding experts, archive etc.