Service Lunch: The Human Factor: Making the Most of AI Results, Zürich

When it comes to machine learning and AI, the main focus is very often on algorithms, data, and infrastructure. Anyone who has ever brought such a model into production at a larger company knows, however, that for many applications there is another decisive factor which often has a larger impact on the final result than the selection of the ML-model or the hyperparameter tuning in order to optimize the 4th decimal place. And these are the employees who (should) use the results of the model in their daily business.

At Contovista, one of our products is a suite of Machine Learning models for banks which are used to maximise the conversation rate of a product campaign (e.g. credit card campaign). The customers
selected by our models are often contacted directly by the client advisor. Thus client advisors have a substantial impact on the final success of the project.

We have gained a lot of experience in how to improve the cooperation with client advisors to ensure that good AI results lead to good project results. In my talk I would like to share some of these
learnings with you and discuss your opinions, experiences and ideas about this topic.