Emerging Tech: Conversational AI

What is conversational AI?

Conversational AI is a form of artificial intelligence that facilitates human-like dialogue between humans and computers in real-time. It works by combining Natural language processing with software like chatbots, voice assistants or voice agents. Most commonly, it is used to manage customer relationships by reducing customer contact by deflecting to digital, resolving service requests, proactively steering customers to the right channel and empowering agents to deliver services with AI and analytics at their side.

Emerging Applications of Conversational AI

1. Greater advancements in chatbot technology. Customers are no longer satisfied by simple rule-based chatbots. Stronger NLP Conversational AI bots will take precedence as they will be able to decipher complex customer needs and sentiments.

2. Enterprise bots/virtual assistants: Virtual assistants are paving the way for the future of work, and greater adoption is expected within enterprises that rely on routine and non-routine cognitive tasks. Enterprise bots will support tasks such as email management, bookkeeping, calendar management, research, data entry & file storage management.

3. Personalization: As conversational AI bots can carry context across different channels, they will be able to provide personalized recommendations based on a user’s past interactions. This will better enable omnichannel experiences with the ability to cross-sell across platforms or services.

4. Simplification of experiences: As conversational AI can integrate with multiple applications on the backend, they can easily reduce touchpoints between multiple applications as they become the single access point.

Potential Drawbacks

1. Conversational AI requires significant training and large data sets to support the domain in which they are used. The process to train a conversation AI bot can be lengthy – but is a necessary process to reduce potential bias.

2. At present, conversational AI cannot handle complex queries or hold conversations.

3. Conversational AI deals with huge amounts of user data and is vulnerable to security breaches. Subsequently, applications must be built with strong security and privacy standards.

Lastly, the greatest drawback for the users themselves is that conversational AI chatbots are just not human. While this is of course obvious, some end users still desire human interaction with customer service representatives that can empathize and understand complex situations and act accordingly. While attempts have been made to make chatbots more “human-like” – this push has often highlighted the mechanical nature of this technology.

Additionally, at present, conversational AI cannot handle complex questions or tasks. If they encounter a situation or question that is unfamiliar to them, they will often perform incorrectly.