While these solutions are adept at automating the customer service process and cutting costs, their limited functionality means they have generated little value wider business context – until now. A new generation of technologies has been developed to not only service customers more effectively, but also to optimize human resource management and employee enablement.
Even now that Conversational AI (CAI) technologies have arrived on the scene to take user experience (UX) to the next level, the truth is, that many individuals will still mistake them for run-of-the-mill Bots. The result of this is that some organizations might invest in the wrong technologies, or else dismiss next-gen solutions that could boost their efficiency.
Beyond just offering first-line support to customers and colleagues, or the conversational acumen of home assistants like Alexa or Siri, newer CAI technologies are capable of fielding a much more complex range of queries, which will no doubt be a great service to organizations in the remote climate.
So, how can businesses tell the difference?
Bots provide basic automated support
Simply put, ChatBots without natural language processing (NLP) and machine learning (ML) support are only capable of recognizing pre-configured keywords, and executing their actions based on these. For simple tasks, like ordering a pizza, for example, traditional solutions are apt – however, these basic technologies would not be appropriate for all businesses. While customers have the option to reply to a ChatBot’s responses, these will often come with a discrete list of pre-programmed responses, which might not fit the bill if you have a more complex offering.
A key distinction that sets CAI platforms apart from ChatBots is the level of human intervention required to function effectively. While CAI technologies will learn continuously and become more intelligent based on their interactions, Bots require the input of programmers to work, and may struggle to understand semantics at the same level.
For example, if a company is looking for a solution to assist with their onboarding and training processing, allowing new hires and current members of staff to ask questions about their role on the go, a ChatBot might not be the most appropriate solution, given the potential for questions that fall outside the domain of these pre-programmed responses. In this situation, a more complex or open-ended query would cause the system architecture to falter.
Looking to Conversational AI in the remote work arena
On the other hand, given that they rely on more complex neural network technologies, CAI platforms have an improved ability to understand the specific context of a conversation, without relying on phrases or inbuilt keywords. Ultimately, this means that employees and customers alike will probably have more luck asking specific questions that a run of the mill ChatBot might have struggled with. As such, this has expanded the horizons for conversational AI into domains where less structured support may be required, and where ChatBots haven’t served particularly well in the past.
In the remote working climate, this is particularly useful. Given that many teams will still be scattered for at least part of the working week, the use of CAI solutions means that individuals will be able to receive the support they require, without needing to rely on lengthy Zoom meetings. Sales executives, for example, may need to have an expansive knowledge about product USPs, as well as an ability to respond quickly to questions from prospective clientele. Should an individual in this line of work have a query, or need a refresher on their knowledge, a CAI platform would serve especially well to effortlessly impart knowledge or walk a user through a procedure.
Up-and-coming NLP technologies will allow users to quickly ask questions about a product’s USP, say, and receive the answers immediately – which should be a great help to those working in the B2B sales arena, for example. What’s more, they will be able to work with open-ended questions and receive real-time support through personalised, two-way communication. If the conversational agent doesn’t understand something, it is capable of asking users to clarify their query, or provide more information so that it can offer better support
For this reason, I suspect that in the years to come, Conversational AI will open up a lot of doors for organizations looking to provide first-class learning and development (L&D), which is tailored to each individual employee. As they develop, these systems will be able to interrogate knowledge graphs to understand the things that make each worker different – our accents, idiolect, and our own individual ways of conversing with one another. Ultimately, the future is bright for Conversational AI, and companies can expect to find new and innovative solutions in the coming years that deliver positive experiences to both customers and employees.
Source: technative.io
