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Course Outline
AI Fundamentals: Key Concepts, Variations, and Common Misunderstandings
- Clarifying what artificial intelligence does and does not do
- Distinguishing between narrow AI and general AI
- Understanding machine learning, deep learning, and data science
- Explaining machine learning mechanisms without technical jargon
Generative AI and AI Agents in the Business Context
- The capabilities and boundaries of generative AI
- Understanding AI agents and their operational mechanics
- Typical business applications of generative AI
- Hallucinations and the current limitations of AI tools
Data Readiness: The Basis for AI
- Structured versus unstructured data
- Data quality and its essential dimensions
- Key data governance principles for managers
- The importance of establishing data readiness before AI deployment
Unlocking Business Value through AI
- The AI opportunity matrix
- Value chain analysis for identifying AI use cases
- Primary and supporting business activities
- Processes that yield the highest value
AI Success Stories and Key Insights
- Real-world AI applications across various business functions
- Factors contributing to successful AI implementations
- Common failure patterns and strategies to prevent them
Workshop: Spotting AI Opportunities by Department
- Mapping departmental processes and identifying pain points
- Developing AI use case ideas for each business area
- Completing an AI opportunity canvas
- Sharing and debating findings across different departments
Prioritizing AI Use Cases for Optimal Value
- Scoring value against feasibility
- Balancing quick wins with strategic investments
- The AI project funnel approach
- Selecting the initial use cases to execute
AI Governance: Roles, Committees, and Accountability
- Determining who should lead AI efforts in the organization
- Defining governance roles, committees, and duties
- Center of Excellence models versus distributed ownership
- Best practices for effective AI governance
Security, Risk, and Responsible AI
- Information security and data protection constraints
- Conducting risk assessments for AI initiatives
- Ethical guidelines and the practice of responsible AI
- Culturing trustworthy AI systems
Preparing an AI-Ready Organization
- Evaluating AI maturity levels
- Required skills and competencies for the AI journey
- Change management and organizational cultural readiness
- The AI strategy cycle
Workshop: Developing the AI Implementation Roadmap and Action Plan
- Synthesizing the opportunity map
- Outlining phases, quick wins, and key milestones
- Assigning ownership, metrics, and governance checkpoints
- Drafting the initial roadmap and subsequent steps
Requirements
- No prior technical or programming background is necessary.
- A genuine interest in applying AI within a business or management setting.
Target Audience
- Senior managers and department heads.
- General managers and C-suite executives.
- Leaders overseeing digitalization and transformation projects.
16 Hours
Testimonials (1)
The trainer is patient and very helpful. He knows the topic well.
