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Course Outline
Day 1 — AI Fundamentals and Business Applications
Module 1 — Introduction to Artificial Intelligence
- Defining AI and common misconceptions
- Types of AI systems
- Generative AI and Large Language Models
- Separating AI myths from reality
- Current trends in AI business adoption
- Opportunities and limitations of AI
Module 2 — AI in Contemporary Business Operations
- How organizations utilize AI today
- AI applications in manufacturing and operations
- AI in sales and customer engagement
- AI in HR and talent acquisition
- AI in procurement and logistics
- AI in finance and financial reporting
- AI for quality management and regulatory compliance
Practical Exercise
Participants experiment with AI tools for:
- text summarization,
- automated report generation,
- email drafting,
- workflow assistance,
- document analysis,
- meeting note compilation,
- and operational planning support.
Day 2 — Enhancing Productivity and Automating Workflows with AI
Module 3 — Boosting Productivity via AI
- AI assistants tailored for managers
- Prompt engineering techniques for business professionals
- Crafting effective business prompts
- Leveraging AI for:
- reporting,
- planning,
- creating presentations,
- documentation,
- meeting preparation,
- supporting decision-making
Module 4 — Data Analysis and Business Insights
- Conducting business analysis with AI
- Extracting key information from documents and spreadsheets
- AI-assisted forecasting and trend identification
- KPI monitoring and operational insights
- Managing structured and unstructured business data
Practical Workshop
Teams tackle realistic business scenarios:
- production reporting,
- sales forecasting,
- supplier analysis,
- HR documentation management,
- operational dashboard creation,
- and quality issue resolution.
Participants construct practical AI-enhanced workflows tailored to their specific departments.
Day 3 — Leveraging AI for Operations, Planning, and Decision-Making
Module 5 — AI in Operational Management
- Enhancing operational efficiency with AI
- Workflow optimization strategies
- Inventory and warehouse management support
- Concepts of predictive maintenance
- Process standardization techniques
- AI-assisted decision-making frameworks
Module 6 — Department-Specific AI Applications
Production and Operations
- Real-time production monitoring
- Root-cause analysis
- SOP (Standard Operating Procedure) generation
- Operational reporting automation
Sales and Business Development
- Lead qualification processes
- Proposal drafting and generation
- Customer communication enhancement
- Competitive landscape analysis
Human Resources (HR)
- Drafting job descriptions
- Interview preparation support
- Training plan development
- Internal communication strategies
Finance and Accounting
- Financial summary generation
- Invoice and document analysis
- Regulatory compliance support
- Automated financial reporting
Quality Management
- Analyzing nonconformities
- Documentation assistance
- Audit preparation support
- Risk tracking and monitoring
Practical Workshop
Participants design:
- one AI use case for their department,
- one automation opportunity,
- and one initiative aimed at measurable productivity improvement.
Day 4 — AI Governance, Risk Management, and Implementation Strategies
Module 7 — AI Governance and Regulatory Compliance
- Principles of responsible AI usage
- Data privacy and confidentiality protocols
- Risks associated with generative AI
- Establishing AI governance policies
- The role of human oversight and validation
- Understanding the EU AI Act regulations
- Ethical and operational considerations in AI deployment
Module 8 — Practical AI Implementation Guide
- Strategies for introducing AI within an organization
- Identifying quick wins and early successes
- Selecting appropriate tools and processes
- Navigating change management challenges
- Evaluating ROI from AI initiatives
- Developing an AI adoption roadmap
Group Exercise
Teams evaluate:
- which processes are suitable for AI and which should be avoided,
- potential operational risks,
- implementation priorities,
- and challenges related to internal adoption.
Day 5 — Business Simulation and AI Strategy Workshop
Module 9 — AI Strategy Workshop
Participants collaborate in teams to develop:
- department-specific AI action plans,
- implementation priorities,
- risk assessments,
- and measurable operational goals.
Final Practical Project
Teams present:
- a comprehensive AI implementation proposal,
- anticipated business benefits,
- expected operational impact,
- identified risks,
- and a strategy for adoption.
Final Discussion and Strategic Recommendations
- Actionable next steps for AI adoption
- Identifying internal AI champions
- Recommended tools and workflow enhancements
- Long-term development of AI capabilities within the organization
Requirements
Intended Participants
- 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
