Artificial intelligence in business: potentials, use cases, value contributions

• What is artificial intelligence?
• AI as the most important innovation for digital change
• Relevance: What AI means for companies
• Perspectives: What AI will achieve
• Prerequisite: data and trust
• Use data sources outside the organization
• Effects: How AI is changing the rules
• The future: what's next for AI

• From the beginnings to today's LLMs
• Principles of human learning
• Learning methods in machine learning
• Artificial neural networks (KNN)
• Deep learning explained in a nutshell
• Residual Networks (ResNet)
• Convolutional Neural Networks (CNN)
• Generative Adversarial Networks (GAN)
• Recurrent Neural Networks (RNN)

• Emotional and cognitive value contributions through AI
• The relationship between humans and AI
• The AI periodic system for companies
• Group 1: "Assess"
• Group 2: "Infer"
• Group 3: "Respond"

After reflecting on the content from the first self-study phases, the focus is on the concrete application of AI in a business context. Using the AI Project Canvas, participants get to know a tool that they can use to describe their AI project in a structured and methodical way. The AI Project Canvas is a proven methodology for starting a new AI project, e.g. to get involved in stakeholders.

• Use of AI in various areas of the company 
• Four fields of action for management 
• Developing fields of application with the AI Project Canvas 
• Understanding fields of application by example: 20 AI hacks 
• creative services with AI 
• Simplification and assistance through AI 
• Using AI for analyses 
• AI helps to avoid errors 
• Using AI for forecasts 
• Productive fields of application for AI 
• How do employees benefit from AI?

• Challenges in AI projects 
• Why AI projects fail 
• Special features of AI projects 
• The AI trend radar: application and how it works 
• The AI trend radar for financial service providers 
• The AI trend radar for insurance companies 
• The AI trend radar for healthcare companies 
• Create the AI trend radar for your own industry 
• Key learnings for the AI maturity path

In the final live webinar - after reflecting on the self-study unit and answering open questions - the prepared AI Project Canvas is presented and discussed. The feedback from the participants and the:der trainer prepares the participants intensively for a possible implementation of their individual AI project.