The Evolution of Conversational Design: Embracing AI Training for a New Era

In the fast-evolving world of voice technology, one thing has become abundantly clear: conversational design, as we once knew it, is dead. Replaced by AI training, the way we approach voice experiences with machines has fundamentally shifted, and it’s time we embrace that change.

Moving Beyond the "Intent" Model

The traditional “intent” model, a staple of early Voice AI systems, was based on the concept of mapping user intents to predetermined functions. Designers were tasked with predicting every possible intention a user might have during an interaction and assigning it a specific response or action. This framework, while innovative at the time, had significant limitations.

Designing for every possible intent became an incredibly complex process, leading to rigid conversational flows. Users were often met with limited responses, as the system could only operate within the narrow boundaries of its pre-designed intents. This often resulted in robotic, context-lacking interactions—leaving much to be desired in terms of user experience.

Enter Generative AI: A New Approach

With the rise of Generative AI, we now have the opportunity to move beyond these restrictive, intent-based designs. The ability of AI to learn and adapt through training opens the door to more dynamic, flexible conversations that can evolve over time.

At Chordia, we’ve embraced this shift by adopting a “topic”-based approach. Instead of focusing on predicting specific user intents, our AI models are trained to engage in conversations on defined topics. This approach allows for richer, more fluid interactions—where the AI can go deep into the subjects it’s trained on and gracefully avoid areas outside of its scope.

The Benefits of Topic-Based AI Training

This topic-driven model has several key advantages:

1. Natural Conversations
   By focusing on broader topics rather than individual intents, the AI can respond in a way that feels more organic. Conversations aren’t limited to pre-scripted responses but instead evolve naturally based on the user’s input and the topic being discussed.
2. Increased Flexibility
   Unlike the rigid structure of intent mapping, topic-based AI can adapt to new information and changing contexts during a conversation. This allows for a more personalized experience, as the AI can adjust its responses based on the direction of the conversation.
3. Enhanced Focus
   Our models know what they’re good at—and just as importantly, what they’re not. By training AI on specific topics, we ensure that it provides valuable insights on areas it’s been trained for, while seamlessly redirecting or avoiding discussions outside its expertise.

The Future of Conversational Design

As we continue to see advancements in AI, it’s clear that the traditional ways of designing voice experiences need to evolve. At Chordia, we believe that AI training is the future of conversational design. By moving away from rigid intent models and embracing topic-driven interactions, we can create more meaningful, engaging conversations for users.

It’s time to rethink how we approach voice experiences—by focusing on what’s next, we can unlock the full potential of AI and create truly impactful interactions.