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Course Outline
Day 1 — Introduction to AI and Business Applications
Module 1 — Introduction to Artificial Intelligence
- What AI is and what it is not
- Types of AI systems
- Generative AI and Large Language Models
- AI myths vs reality
- Current business trends in AI adoption
- Opportunities and limitations of AI
Module 2 — AI in Modern Business Operations
- How companies use AI today
- AI applications in manufacturing and operations
- AI in sales and customer communication
- AI in HR and recruitment
- AI in procurement and logistics
- AI in finance and reporting
- AI for quality management and compliance
Practical Exercise
Participants test AI tools for:
- summarization,
- report generation,
- email drafting,
- workflow support,
- document analysis,
- meeting notes,
- and operational planning.
Day 2 — Practical AI Productivity and Workflow Automation
Module 3 — AI-Powered Productivity
- AI assistants for managers
- Prompt engineering for business users
- Creating effective business prompts
- Using AI for:
- reporting,
- planning,
- presentations,
- documentation,
- meeting preparation,
- decision support
Module 4 — Data Analysis and Business Insights
- Business analysis with AI
- Extracting information from documents and spreadsheets
- AI-assisted forecasting and trend analysis
- KPI monitoring and operational insights
- Working with structured and unstructured business data
Practical Workshop
Teams work on realistic business scenarios:
- production reporting,
- sales forecasting,
- supplier analysis,
- HR documentation,
- operational dashboards,
- and quality issue analysis.
Participants build practical AI-supported workflows relevant to their departments.
Day 3 — AI for Operations, Planning, and Decision-Making
Module 5 — AI in Operations Management
- AI for operational efficiency
- Workflow optimization
- Inventory and warehouse support
- Predictive maintenance concepts
- Process standardization
- AI-assisted decision-making
Module 6 — Department-Specific AI Applications
Production and Operations
- Production monitoring
- Root-cause analysis
- SOP generation
- Operational reporting
Sales and Business Development
- Lead qualification
- Proposal generation
- Customer communication
- Competitive analysis
HR
- Job descriptions
- Interview preparation
- Training plans
- Internal communications
Finance and Accounting
- Financial summaries
- Invoice/document analysis
- Compliance support
- Reporting automation
Quality Management
- Nonconformity analysis
- Documentation support
- Audit preparation
- Risk tracking
Practical Workshop
Participants design:
- one AI use case for their department,
- one automation opportunity,
- and one measurable productivity improvement initiative.
Day 4 — AI Governance, Risk, and Implementation
Module 7 — AI Governance and Compliance
- Responsible AI usage
- Data privacy and confidentiality
- Risks of generative AI
- AI governance policies
- Human oversight and validation
- Understanding the EU AI Act
- Ethical and operational considerations
Module 8 — Practical AI Implementation
- How to introduce AI inside an organization
- Identifying quick wins
- Selecting tools and processes
- Change management considerations
- Measuring ROI from AI initiatives
- Building an AI adoption roadmap
Group Exercise
Teams evaluate:
- which processes should or should not use AI,
- operational risks,
- implementation priorities,
- and internal adoption challenges.
Day 5 — Business Simulation and AI Strategy Workshop
Module 9 — AI Strategy Workshop
Participants work in teams to create:
- department AI action plans,
- implementation priorities,
- risk assessments,
- and measurable operational goals.
Final Practical Project
Teams present:
- a real AI implementation proposal,
- expected business benefits,
- operational impact,
- risks,
- and adoption strategy.
Final Discussion and Recommendations
- Next steps for AI adoption
- Internal AI champions
- Recommended tools and workflows
- Long-term AI capability development
Requirements
Target Audience
- Production Managers
- Strategic Planning Managers
- Sales and Business Development Leaders
- HR Managers
- Procurement and Warehouse Managers
- Innovation Leaders
- Finance and Accounting Professionals
- Quality Managers
- Operational and Administrative Managers
35 Hours
