Applied AI: From fraud detection and credit risk assessment to defect classification and quality control – What are the use & business cases of machine learning in practice?

Natural Language Processing & Voice Recognition: Which use cases of Neural Networks, Computer Vision, Voice Recognition are applied in practice? What are the challenges regarding AI in voice assistants?

Simulation, Testing & Validation: How should datasets be structured and processed in order to develop robust machine learning models?

AI & Machine Learning Security: How can AI and machine learning algorithms be secured and threats and vulnerabilities be identified at an early stage?

AI-driven infrastructure & hardware: What are the technical requirements for the systems and how can the optimal composition of the technology stack be achieved?

Predictive Analytics: How can organizations effectively use predictive analytics or transition to adopting more advanced AI solutions?

Customer Journey & Data: How can data integration be optimized across BUs, systems and tools? How do you deal with unstructured and poor quality data in the context of the Customer Journey?

Generative AI: How does generative AI contribute to the creation of predictive models that support decision-making and information sharing in companies? What are the potential benefits and limitations of this application?