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The Evolution of the AI Conversation Agent

The Evolution of the Intelligent Conversation Agent AI and Machine Learning

Conversation Agents have been around long enough for the public to know the difference between a cost-saving solution and a value-added customer-focused experience that makes everyday life easier. It's up to businesses to implement conversation agents that don't frustrate customers and also increases your bottom line. 

One of my first experiences with chatbots was in an interesting exchange between myself and one of the leading minds in the AI world and an IBM Fellow, Watson CTO Rob High, while I lead the Watson and AI competency center in Eastern Europe.   Without getting into the details, what I came out of that meeting with is a much more pragmatic understanding of the purpose of chatbots or conversation/virtual agents. 

Having also lead the Design Thinking chapter for the region, I took this pragmatic discussion to heart and wanted to evolve these ideas with user experience in mind. Working at V-Soft Consulting  the notion of building compelling experiences that thoroughly WOWed users and provided compelling reasons for them to interact with it again became a cornerstone of our product development strategy for our VERA conversation agent.

Conversation Agents Must be Better Than Humans

The idea is, we don't want the user to be frustrated when interacting with the agent. Instead we want an agent that is superior to simply interacting with a human. Because otherwise, what’s the point right?

If the consumer is just as satisfied or slightly dissatisfied with the chatbot interaction they are left with a perception that the bot is just a cost-cutting measure for the organization. If there experience is as good or slightly above that of a real person, there is no differentiator there and an equivalent human to human experience with another company is just as good. 

Moreover, the gap between status-quo systems and new technologies being adopted, from the perspective of the customer is much bigger and more abstract than quantifiable value. It reaches deep into psychological behaviors of people and their comfort levels with communicating with a human versus a bot. This is especially true when you have artificial intelligence agents looking to replace human-interaction.

Advanced Technology for Conversation Agents

So to bridge this gap and create compelling WOW experience that motivates the user to return for new experiences with our conversation agent we incorporated various design features that are central to enhancing the user experiences.

User Insights Model

This is an Artificial Intelligence platform that collects historical insights on specific users, their experiences, and system interactions as well as external data relevant to understanding the specific user and their inquiries and provides an enhanced dialogue interaction through selective language (speaking to user knowledge and linguistic experience) and through additional information not explicitly asked for (providing them information it believes is also necessary to communicate that wasn’t explicitly asked).

Unified Knowledge Curation and Presentation

In order to make the experience of a conversation agent thoroughly equivalent to a human interaction, and not just in phone calls with a ticketing agents, but a true Virtual assistant, the user should not be limited to simple text interactions or static information output. The unified knowledge curation and presentation platform provides the ability to interlink various forms of data (video, images, text etc.) and present it to the user in a way that they can then further interact with. So imagine being able to request information about a particular product, retrieve a diagram of this product, and then interact with that diagram to further engage the agent with additional questions.

The notion that next-generation conversation agents, virtual agents, or chatbots (call them what you want, since ultimately we are talking about the same thing in different evolutionary states), are not static dialogues with dummy interactions but true AI tools that learn from their interactions, that provide relevant information that you asked for and provide information you didn’t even know you wanted.

To learn more about these two features and more on how VERA conversation agents work visit our website.

About Author

Konrad Konakonrad konarski practice head artificial intelligence and internet of thing for V-Soft Consultingrski  is V-Soft's Practice Head for AI & IoT where his cumulative expertise is used to commercialize and deliver industry-changing solutions for businesses. Konrad has worked with emerging technologies for more than 15 years. As a successful entrepreneur, engineer, business professional, and thought leader, he has a holistic perspective on delivering AI solutions that bring tangible value to customers. 

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Topics: Artificial Intelligence, Tech Trends, AI, IoT, Internet of Things

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