For people to trust using AI models, we need to make AI models transparent and understandable. Using well-considered interactions and visualisations you will find out how to create explainable AI models. We will look at some example cases in the health care sector and marketing sector. Illustrating how UX affects end-users perception of your AI models.

Just a few years back, when we talked about Artificial Intelligence for Customer Service, what we probably had in mind was “just” chatbot. The fast development of AI and Machine Learning brings and will keep bringing much more exciting capabilities to the contact center to improve both customers and agents experience. Capabilities such as : - Predictive Routing : matching customers with the best available resource by predicting business outcome - Predictive Engagement : predicting user behaviour, shifts in interests or the likelihood of events on the web to anticipate when to offer agent support - Automated forecasting and scheduling : building forecast and schedule for the contact center in under five minutes using AI - Agent Assist : listening and analysing the content and context of a live interaction to provide agents prompts, hints and tips in real time … Join this session to learn more about the impact of AI on Customer Service and Customer Experience

Despite the recent progress in Natural Language Processing, implementing NLP projects for business remains a challenge. Even when reliable machine learning approaches exist, it is often hard to deal with the limited availability of data or to fit the NLP application in an existing workflow. In his presentation, Yves will pierce the hype to find out how NLP can best be applied to your business. Through a number of case studies, he will discuss how major hurdles like data scarcity can be overcome and how you can get the most out of your use case.