Course Outline
AI Basics: Core Concepts, Types & Common Myths
- Clarifying what artificial intelligence is and is not
- Distinguishing between Narrow AI and general AI
- Understanding machine learning, deep learning, and data science
- Explaining how machine learning operates without technical jargon
Generative AI & AI Agents in the Enterprise
- Capabilities and constraints of Generative AI
- How AI agents function
- Typical business applications for Generative AI
- Understanding hallucinations and the boundaries of current tools
Data Readiness: The Bedrock of AI
- Structured vs. unstructured data
- Key dimensions of data quality
- Essentials of data governance for managers
- The importance of data readiness prior to AI adoption
Unlocking Business Value with AI
- Utilizing the AI opportunity matrix
- Conducting value chain analysis for AI use cases
- Focus on primary and supporting activities
- Identifying processes that yield the highest value
Success Stories & Key Takeaways from AI Implementations
- Real-world AI applications across various business functions
- Factors behind successful AI implementations
- Recognizing common 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
- Completing an AI opportunity canvas
- Sharing and debating findings across departments
Prioritizing AI Use Cases for Optimal Value
- Scoring based on value versus feasibility
- Distinguishing between quick wins and strategic bets
- The AI project funnel approach
- Selecting the initial use cases to pursue
AI Governance: Roles, Committees & Accountability
- Determining who should lead AI initiatives in the organization
- Defining governance roles, committees, and responsibilities
- Center of Excellence vs. distributed ownership models
- Best practices in AI governance
Security, Risk & Responsible AI
- Constraints related to information security and data protection
- Risk assessment for AI projects
- Ethical guidelines and responsible AI practices
- Building trust in AI systems
Cultivating an AI-Ready Organization
- Evaluating AI maturity levels
- Required skills and competencies for the AI journey
- Change management and cultural preparedness
- The continuous AI strategy cycle
Workshop: Developing the AI Implementation Roadmap & Action Plan
- Consolidating the opportunity map
- Defining phases, quick wins, and key milestones
- Assigning owners, metrics, and governance checkpoints
- Formulating the initial roadmap and next steps
Requirements
- No prior technical background or programming experience is necessary.
- A genuine interest in applying AI within a business or managerial context.
Target Audience
- Senior managers and department heads.
- General managers and C-suite executives.
- Leaders overseeing digitalization and transformation projects.
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
