From training data to knowledge-driven

Overview

One of the most common questions we hear from customers is:

“How is an AI Agent trained to do a specific task? How does it learn?”

Behind that question often lies a concern:

• Will we have enough training data?

• Will the process be too complex or require highly specialised skills?

These concerns are understandable - because, for years, the narrative around AI was framed around data-hungry models.

Businesses were told that success meant identifying large datasets, selecting the right machine learning technique, and generating a model capable of classifying or predicting outcomes.

This framing emphasised “training” and “learning” as if AI systems behaved like people. In practice, it meant organizations spent huge amounts of effort collecting, curating, and maintaining datasets to make AI work. Generative AI - and in particular, its application to Conversational AI Agents - fundamentally changes this picture.

Want this guide?

Complete this form and download our white paper for free.