Applied Artificial Intelligence (AI) for Managers, Systems Analysts, and Project Teams

AAI - Version:1

Description

Artificial Intelligence is rapidly transforming the way organizations operate, make decisions, and develop solutions. Alongside the excitement and innovation, there is often confusion: Which tools are truly beneficial? How can AI be integrated into daily workflows without becoming a technologist? This course is designed to provide clarity. It offers a deep yet accessible introduction to the world of AI, with a strong emphasis on practical application, process optimization, improved work quality, and smarter decision-making — all without requiring an advanced technical background or coding skills. The learning process combines clear explanations, live demonstrations, and hands-on practice, applying AI across the full lifecycle of organizational systems and projects.

Intended audience

Department and Unit Managers. Systems Analysts, Project Managers, and Information Systems (IS) professionals. Product Managers, Marketing professionals, and QA personnel. Employees and managers interested in boosting productivity through AI.

Topics
Prerequisites
Objectives

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Foundations and Understanding the AI Landscape
- Foundations and Understanding the AI Landscape
  - What is AI? Definition, evolution, and core concepts.
  - Key AI Types: Understanding the main categories and the differences between them.
  - AI Use Cases: Applications in daily life and the corporate world.
  - Advantages, Limitations, and Challenges: Including ethical and organizational considerations.
Generative Tools – Working Smarter and Faster
- In-depth Introduction to Leading Generative AI Tools: GPT, Gemini, Claude, Suno, Kling, and more.
- Effective Prompt Engineering: Thinking, phrasing, and refining results.
- Advanced Workshop: Leveraging Chatbots for administrative and management tasks.
- No-Code Bot Creation: Hands-on workshop for building custom bots.
AI as a Daily Management Tool
- Email Management: Reducing response time, improving phrasing, and managing overload.
- Meeting Summaries: Converting documentation into actionable insights.
- Presentations: Transforming ideas into clear, innovative, and engaging content.
- Document Processing: Analyzing, extracting insights, and creating effective documentation.
- Data Analysis: "Conversing" with data without requiring technical expertise.
- SWOT and Competitive Analysis: Enhanced by AI tools.
- Creativity and Out-of-the-Box Thinking: Using AI for brainstorming and ideation.
Implementation, Innovation, and Organizational Leadership
- Identifying Relevant Use Cases: Pinpointing opportunities within the organization.
- MVP Planning: Designing a Minimum Viable Product with AI assistance.
- Tool Selection: Matching AI solutions to existing organizational needs.
- Defining Smart KPIs: Measuring the success of AI implementation.
- AI-Driven Workplans: Building an organizational roadmap for AI adoption.
Comprehensive Practice – AI in the Systems Analysis Lifecycle
- A cross-functional exercise simulating a real-world project, from ideation to technical planning:
- High-level characterization and definition of business needs.
- Business analysis and requirements writing.
- Decomposition into Epics, Features, and User Stories.
- Mapping organizational processes.
- Conceptual technical characterization.
- Data modeling and database design.
- REST API planning (as both provider and consumer).
- Using AI tools to assist in selecting infrastructures and indexing strategies.

- Provide a fundamental understanding of the AI field and its organizational implications.
- Enable participants to identify real opportunities for using AI in their professional roles.
- Introduce and provide hands-on experience with leading Generative AI tools and AI-driven management and creation tools.
- Develop the ability to analyze, characterize, and design systems using AI tools.
- Provide a practical foundation for the gradual and informed implementation of AI within the organization.