✪ Day 1: Introduction to Artificial Intelligence in Office and Administrative Work

✓ The concept of Artificial Intelligence and its applications in the administrative environment.
✓ The difference between Artificial Intelligence and automation.
✓ Generative AI, Machine Learning, and Natural Language Processing (NLP).
✓ AI applications in correspondence, meetings, report preparation, and data analysis.
✓ The impact of AI on improving administrative efficiency and supporting decision-making.
✓ Challenges of AI adoption, privacy concerns, and output verification.

✪ Day 2: Fundamentals of Professional Administrative Reporting

✓ The concept of administrative reports and their different types.
✓ Characteristics of professional reports and the report preparation cycle.
✓ Operational, executive, analytical, financial, performance, and project reports.
✓ Components of a professional report (executive summary, analysis, key indicators, charts, and recommendations).
✓ Common mistakes in traditional report preparation and how to avoid them.

✪ Day 3: Prompt Engineering for Report Writing

✓ The concept of prompts and how to write effective instructions.
✓ Building context and defining objectives and desired outputs.
✓ Types of prompts for analysis, writing, summarization, recommendations, and comparisons.
✓ Designing professional templates for executive reports, performance reports, project reports, and meeting reports.
✓ Practical applications for transforming raw data into a comprehensive executive report.

✪ Day 4: Artificial Intelligence Tools Used in Report Preparation

✓ AI tools for report writing and drafting (ChatGPT, Claude, Gemini, Microsoft Copilot, and Notion AI).
✓ Tools for meeting summarization, minutes preparation, and report generation.
✓ Using AI tools to monitor meetings and extract decisions and action items.
✓ Comparing tools and selecting the most suitable one based on the type of report.
✓ Practical applications for preparing professional reports using multiple AI tools.

✪ Day 5: Governance, Security, and the Final Practical Project

✓ Governance of AI use in report preparation.
✓ Data privacy, information confidentiality, and ethical considerations.
✓ Validating outputs and understanding the risks of overreliance on AI.
✓ Institutional policies for the use of Artificial Intelligence.
✓ Developing a comprehensive practical project using multiple AI tools.
✓ Building a dashboard, preparing an executive presentation, and delivering recommendations to senior management.