The rise of chatbots has been recent and substantial. B2B and B2C sites now have bots at the ready, asking how they can help you find information or do what you need to do -- and they are often on a first-name basis with you. Chatbots have proven to be one of the ideal use cases for artificial intelligence (AI) and the appeal is obvious. Unlike their human counterparts, chatbots are available 24/7, can simultaneously answer hundreds of queries instantly and come with a one-time cost compared to the continuous cost of employing customer service representatives. Although there is fear that chatbots aren't as accurate as humans, those concerns have been mitigated in recent years as chatbots can now resolve 80% of customer queries without human supervision. And when they get a question they don't know the answer to, the chatbot is able to move the customer to a live representative for resolution.

Nowadays Messenger chatbots can be set up within a few minutes. However, creating a high-quality customer service chatbot takes some time and professional effort. To train a chatbot the right way, you need a lot of input. This input is fed to chatbots through data that is available everywhere in today's online world. Yet, for machines to be able to make sense of this data, it has to be structured in a readable and usable way.

Many global enterprise companies are benefiting from deploying useful chatbots for customer service, marketing, human resources, communications, and scheduling. Customer service chatbot applications are the most popular, followed by using chatbots for marketing purposes. Many companies using chatbots for marketing are finding them effective in personalizing the experience and improving sales results. Another place to use a chatbot for enterprise businessefforts is in human resource management as a recruitment tool. Chatbot technology can be used effectively to communicate with both the public and employees.