AI Strategy Training

Day 1

Introduction to AI

• The Concept of Artificial Intelligence
• The History and Development of AI
• AI Tools
• Areas of AI Application
• What Does AI Offer Us and How Can We Make the Most of It?
• The Social Impact of AI
• How Does AI Affect My Company?
• AI and Personal Efficiency

AI Technologies

• Generative AI
• Large Language Models (LLM)
• Deep Learning
• Machine Learning

Artificial and Natural Intelligence

• The Impact of AI on Organizational Operations
• Areas of AI Application in Business Organizations
• Examining the Impact on Specific Operational Areas
• How Does AI Change Organizational Operations?
• What is AI good at, and in what ways is it better?
• Human–machine collaboration, division of labor
• How can AI be integrated into organizational operations and processes? 

Areas of AI application

Perception

• Image recognition, computer vision
• Speech recognition
• Text recognition, processing 

Data processing, analysis

• Data analysis 
• Simulations 
• Expert systems, decision support 
• Reporting

Content generation

• Copywriting
• Software development
• Web development
• Product development

Autonomous devices

• Robots
• Self-driving cars
• Software robots (RPA)
• AI agents
• Humanoid robots

Applications of AI agents

Day 2

Using AI to Boost Personal Productivity

• AI Assistants
• ChatGPT, Copilot, Gemini
• AI Prompting
• How can you teach AI to ask the right questions?
• Content Creation, Copywriting
• Note-taking, Reminders, and Summaries
• Processing and answering inquiries and questions
• Processing source data and texts
• Task tracking
• Automating workflows
• How to manage your tools in a system?
• Case studies, best practices
• AI-based data processing exercise

Areas of AI application

• Customer service, chatbots
• Marketing 
• Sales, quote preparation
• Administration
• HR, recruitment
• Finance, controlling, risk management
• Manufacturing, logistics
• Quality control
• Predictive maintenance 
• Software development, low-code and no-code development
• Product development
• Diagnostics, expert systems 
• Identifying areas of corporate AI application

AI strategy

• AI SWOT analysis 
• AI 

- impact
- prerequisites 
- risks

• Value creation, increasing added value, reducing losses with AI
• Collecting and prioritizing AI implementation ideas
• Rethinking the business model
• AI vision
• Incorporating AI into corporate strategy
• Integrating AI into corporate operations and processes
• Creating an AI implementation roadmap

Issues related to AI implementation

• Data-driven decision-making  
• How does AI affect employees, decision-making authority, and accountability?
• What organizational and individual competencies need to be developed for effective AI implementation
• Strengths and weaknesses analysis
• GDPR, Data Protection, and SecurityThe Legal Framework for AI: The EU AI Act
• Data Security and Compliance in AI Systems
• Ethical AI: Challenges, Pitfalls, and Risks
• Internal AI Governance: Developing Policies

Exam
-    Creating and presenting a personalized AI implementation roadmap  and a written exam