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Course Outline
AI Fundamentals: Concepts, Types and Misconceptions
- What artificial intelligence is and is not
- Narrow AI versus general AI
- Machine learning, deep learning and data science
- How machine learning works without technical jargon
Generative AI and AI Agents in Business
- Generative AI capabilities and limitations
- AI agents and how they work
- Common business applications of generative AI
- Hallucinations and the limits of current tools
Data Readiness: The Foundation for AI
- Structured and unstructured data
- Data quality and its key dimensions
- Data governance essentials for managers
- Why data readiness comes before AI
Where AI Creates Business Value
- The AI opportunity matrix
- Value chain analysis for AI use cases
- Primary and supporting activities
- Processes that generate the most value
AI Success Cases and Lessons Learned
- Real-world AI applications across business functions
- What made successful implementations work
- Common failure patterns and how to avoid them
Workshop: Identifying AI Opportunities by Department
- Mapping department processes and pain points
- Generating AI use case ideas for each business area
- Completing an AI opportunity canvas
- Sharing and discussing findings across departments
Prioritizing AI Use Cases for Maximum Value
- Value versus feasibility scoring
- Quick wins versus strategic bets
- The AI project funnel
- Selecting the first use cases to pursue
AI Governance: Roles, Committees and Accountability
- Who should lead AI in the organization
- Governance roles, committees and responsibilities
- Center of Excellence versus distributed ownership
- Best practices for AI governance
Security, Risk and Responsible AI
- Information security and data protection constraints
- Risk assessment for AI initiatives
- Ethical guidelines and responsible AI use
- Building trustworthy AI
Building an AI-Ready Organization
- Assessing AI maturity
- Skills and competencies for the AI journey
- Change management and cultural readiness
- The AI strategy cycle
Workshop: Creating the AI Implementation Roadmap and Action Plan
- Consolidating the opportunity map
- Defining phases, quick wins and milestones
- Assigning owners, metrics and governance checkpoints
- Producing the initial roadmap and next steps
Requirements
- No prior technical or programming knowledge is required.
- An interest in applying AI within a business or management context.
Audience
- Senior managers and department heads.
- General managers and executives.
- Leaders responsible for digitalization and transformation initiatives.
16 Hours
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.
