Is chatbot able to enhance employee experience in driving real-time engagements

Every business needs a workforce that’s ready to respond and there are 2 billion conversations taking place over digital channels every day. Digital Conversations have fundamentally changed the way we communicate and interact today. Be it asking Alexa to play our favourite song or ordering pizza over Facebook Messenger or getting styled with real time advice over interactive conversational apps, the way we get things done has changed. This new behaviour is already driving a generational shift in how consumers connect with businesses today. They are expecting natural and personal conversations in every interaction with you, just the way they converse with their friends and family. Chatbots are computer programmes which mimic conversations with people using Natural Language Processing (NLP) and Artificial Intelligence. They can interact with people on the internet by initiating a conversation. They act as digital assistants that address queries regarding specific products or services.

Sometimes chatbots are for our better usage and at times it is going to get worse. It has become ubiquitous in our everyday lives. Conversational AI is rapidly growing and increasingly sophisticated technology, but its aims are quite simple and straightforward: productive interactions with customers and clients that are casual and informal, friendly and relaxed—human, in other words. There are potential risks also associated with the chatbots and it is well recognised with various threats and vulnerabilities. Threats that a chatbot could pose include spoofing/impersonating someone else, tampering of data, and data theft.

The chatbots can answer fast on your behalf to help keep consumers happy and engaged. At the same time, the system can become vulnerable and open to attacks when it is not well maintained, has poor coding, lacks protection, or due to human errors.

It is all about riding the next-gen technology wave to operational success. From the consumer-facing to manufacturing industries, there is no dearth of chatbot examples like Siri, Cortana, and Alexa. It is common knowledge that chatbots interact with users through text or voice channels in a natural language. Every organisation or business line wants a perfect solution for their business problems. However, do organisations design a perfect solution? Getting the design right is one of the most critical aspects of chatbot deployment. The underlying design of the chatbot solution and the associated natural language processing (NLP) differentiates successful chatbot implementation from a failed one. There are security protocols in place to increase chatbot security. The process is similar to any other system that involves introducing sensitive data in that respect.

As per Deloitte, lack of data and sufficient information that needs to be fed into a chatbot is a major roadblock hindering its performance. If a bot is being built to respond to user queries related to HR policies, information across different policy documents should be readily available in a way that can be consumed by the bot. Many advanced chatbot platforms offer a document extraction capability whereby the policy documents can be directly integrated with the chatbot to provide responses. The challenge is to know what the end-users might be interested in and prepare that information.

So, adoption would be low if users do not receive relevant information from the bot, resulting in fewer chances of improving accuracy by learning from user interactions. It is advisable to start implementing a chatbot solution with about 80% of the data and then collect the remaining over time.