Intelligent chatbots spark as much hope as they do questions!
Linear vs. Non-linear
Do intelligent chatbots really exist?
First, it is important to distinguish between two major families of chatbots. Linear chatbots, which became widespread in the 1990s, were installed on websites to help visitors navigate site content. Imprecise, these tools were swept aside by search engines with far higher performance and much simpler usability.
From the 2010s onward, a new generation of conversational robots emerged thanks to advances in cognitive technologies associated with natural language understanding (NLU). These non-linear chatbots, wrongly labeled as intelligent chatbots, became widespread, driven by the massive use of messaging applications. We no longer speak to each other; we write. This is the case for 62% of Americans under 30 who say they prefer messaging over phone calls when communicating with friends. Conversational interfaces are definitively the interfaces of the future for millennials.
Benefits for the User
The major difference between these 2 types of chatbots lies in the user experience. In the case of a linear chatbot, the user is confined to a passive role in which they simply respond to the chatbot’s prompts. The distance between a question and its answer is notably large, given the constrained nature of the experience. These chatbots follow journeys built as decision trees, which require the user to perform a number of actions before obtaining a relevant answer.
There is another form of interaction. By using artificial intelligence (AI), it is possible to abandon the logic of decision trees. Integrating NLP technology into the experience fundamentally changes the user experience, simplifying it and making it far more human. We then speak of “intelligent chatbots” since they are capable of analyzing and interpreting the intentions contained in a sentence expressed in natural language, and of triggering the necessary actions to produce a relevant response. The distance between a question and a relevant answer is very short.
Google seems to have understood the value of better understanding user intent through natural language analysis. In recent months, you obtain results much faster, directly on the search results presentation interface.
Toward a Revolution ?
This is a disruptive innovation that explains the public’s enthusiasm for this new generation of interfaces. Beyond the natural hype surrounding this kind of phenomenon, it represents a genuine revolution for the user.
For the first time, interfaces are disappearing. It is a paradigm shift: machines understand humans, not the other way around.
This is one more step toward the ultra-digitization of our physical environments.
Environments that will ultimately see graphical interfaces disappear in favor of natural language interfaces (voice or text). Objects, increasingly connected, will become increasingly intelligent. This is the promise made by natural language understanding technologies, which improve as we explore all the disciplines of artificial intelligence.
Human / Machine interactions will evolve to increasingly resemble Human / Human interfaces. The convergence of conversational technology and the IoT leads us to believe that a new world is emerging.
A world where humans become increasingly impatient, where consumers expect brands to be far more available and capable of offering new services, with strong degrees of personalization and contextualization.
And Tomorrow?
On the brand side, the question arises of their capacity to collect, structure, analyze, and use the enormous volumes of data flowing through these new ecosystems.
Understanding behaviors through deep data analysis will undoubtedly be one of the differentiating factors in increasingly open and competitive markets.
