Course Outline
AI Fundamentals: Key Concepts, Categories and Common Misconceptions
- Distinguishing what artificial intelligence is—and is not
- Contrasting Narrow AI with General AI
- Overview of machine learning, deep learning, and data science
- Understanding machine learning principles without technical jargon
Generative AI and AI Agents in a Business Context
- Capabilities and limitations of Generative AI
- How AI agents function
- Typical business applications of generative models
- Understanding hallucinations and current tool constraints
Data Readiness: The Bedrock of AI Success
- Differentiating between structured and unstructured data
- Key dimensions of data quality
- Essential data governance principles for managers
- The importance of data readiness prior to AI adoption
Identifying AI’s Contribution to Business Value
- Utilizing the AI opportunity matrix
- Conducting value chain analysis for AI applications
- Focusing on primary and supporting activities
- Recognizing processes that yield the highest value
AI Success Stories and Strategic Lessons
- Examining real-world AI applications across various functions
- Factors driving successful AI implementations
- Identifying common failure patterns and mitigation strategies
Workshop: Spotting AI Opportunities by Department
- Mapping departmental processes and identifying pain points
- Brainstorming AI use cases for each business area
- Completing an AI opportunity canvas
- Collaboratively discussing findings across departments
Prioritizing AI Use Cases for Optimal Impact
- Scoring based on value versus feasibility
- Balancing quick wins with strategic long-term bets
- Navigating the AI project funnel
- Selecting the initial use cases for execution
AI Governance: Structure, Committees and Accountability
- Determining leadership responsibilities for AI
- Defining governance roles, committees, and duties
- Choosing between a Center of Excellence and distributed ownership
- Adopting best practices for AI governance
Security, Risk Management and Responsible AI
- Navigating information security and data protection requirements
- Conducting risk assessments for AI projects
- Applying ethical guidelines and responsible AI principles
- Building trust in AI systems
Cultivating an AI-Ready Organization
- Evaluating current AI maturity levels
- Identifying necessary skills and competencies for the AI journey
- Managing change and ensuring cultural readiness
- Understanding the AI strategy cycle
Workshop: Developing the AI Implementation Roadmap and Action Plan
- Consolidating the AI opportunity map
- Establishing phases, quick wins, and key milestones
- Assigning ownership, defining metrics, and setting governance checkpoints
- Finalizing the initial roadmap and determining next steps
Requirements
- No prior technical or programming experience is necessary.
- A genuine interest in leveraging AI within a business or managerial context.
Target Audience
- Senior managers and department heads.
- General managers and executive leadership.
- Leaders overseeing digitalization and transformation efforts.
Testimonials (2)
The trainer is patient and very helpful. He knows the topic well.
CLIFFORD TABARES - Universal Leaf Philippines, Inc.
Course - Agentic AI for Business Automation: Use Cases & Integration
Able to pivot upon audience suggestions - ie able to create a real AI agent scenario on the spot.
