Course Outline
AI Fundamentals: Key Concepts, Variations, and Common Myths
- Defining what artificial intelligence is, and what it is not
- Distinguishing between Narrow AI and General AI
- Understanding machine learning, deep learning, and data science
- Explaining how machine learning functions without technical jargon
Generative AI and AI Agents in a Business Context
- The strengths and constraints of generative AI
- The mechanics of AI agents
- Typical business applications of generative AI
- Hallucinations and the current boundaries of AI tools
Data Readiness: The Cornerstone of AI
- The difference between structured and unstructured data
- Data quality and its critical dimensions
- Essentials of data governance for managers
- The importance of establishing data readiness prior to AI adoption
How AI Generates Business Value
- The AI opportunity matrix
- Value chain analysis tailored for AI use cases
- Primary and support activities in the business context
- Identifying the processes that yield the highest value
AI Success Stories and Key Takeaways
- Practical AI applications across diverse business functions
- Factors that contribute to successful implementations
- Typical failure patterns and strategies to prevent them
Workshop: Spotting AI Opportunities by Department
- Mapping departmental processes and identifying pain points
- Brainstorming AI use case ideas for each business area
- Finalizing an AI opportunity canvas
- Sharing and debating insights across different departments
Prioritizing AI Use Cases for Optimal Impact
- Scoring based on value versus feasibility
- Balancing quick wins with strategic long-term bets
- The AI project funnel
- Choosing the initial use cases to pursue
AI Governance: Roles, Committees, and Accountability
- Determining who should spearhead AI initiatives in the organization
- Governance structures, committees, and duty allocation
- Center of Excellence models versus distributed ownership
- Best practices for effective AI governance
Security, Risk, and Responsible AI
- Constraints regarding information security and data protection
- Risk assessment methodologies for AI projects
- Ethical frameworks and responsible use of AI
- Constructing trustworthy AI systems
Building an AI-Ready Organization
- Evaluating current AI maturity levels
- Required skills and competencies for the AI journey
- Change management and assessing cultural readiness
- The continuous AI strategy cycle
Workshop: Developing the AI Implementation Roadmap and Action Plan
- Consolidating the identified opportunity map
- Setting out phases, quick wins, and key milestones
- Assigning owners, defining metrics, and establishing governance checkpoints
- Finalizing the initial roadmap and outlining next steps
Requirements
- No previous technical or programming experience is necessary.
- A general interest in leveraging AI within a business or management setting.
Target Audience
- Senior managers and department heads.
- General managers and C-suite executives.
- Leaders overseeing digitalization and transformation efforts.
Testimonials (2)
correct way of prompting and including guardrails in instructions.
YEO SHI MIN - ST Engineering Aerospace Ltd
Course - ChatGPT and Microsoft 365 Copilot for Advanced Productivity
Understand AI function n tools to make our job easier. Need to improved AI Chubb such as make analysis n creating presentation
