Session 1: Introduction to AI (2 hours)

• Definitions and history of AI.
• Core components:
• Machine learning.
• Deep learning.
• Natural language processing (NLP).
• Overview of AI trends and future developments in the U.S.

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Session 2: AI in U.S. Business Context (3 hours)

• Key U.S. industries leveraging AI:
• Healthcare (e.g., diagnostic tools).
• Finance (e.g., fraud detection, algorithmic trading).
• Retail (e.g., personalized marketing).
• Case study: AI-driven transformation in a U.S. company
• Group discussion: Potential applications in participants’ organizations

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Session 3: AI Tools and Technologies (1.5 hours)

• Overview of widely used AI platforms:
• Amazon Web Services (AWS), Microsoft Azure, Google Cloud AI.
• Non-technical demonstration of AI tools
• Selecting the right AI tool for U.S. market needs.

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Session 4: Identifying AI Opportunities (1.5 hours)

• Interactive exercise:
• Participants brainstorm AI use cases relevant to their business context.
• Group presentations and facilitator feedback.

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Session 5: AI Strategy and Implementation (2 hours)

• Steps to integrate AI into business operations
• Developing an AI roadmap: Aligning AI initiatives with organizational goals.
• AI’s role in supporting strategic objectives in different business areas.
• Assessing organizational readiness.
• Resource allocation and team collaboration.
• Change management and workforce transformation.
• Best practices for AI implementation in U.S. businesses.

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Session 6: U.S. AI Regulations and Compliance (2.5 hours)

• Key regulations impacting AI:Examples include – specifics subject to state.
• California Consumer Privacy Act (CCPA): Data privacy rights and AI-driven personalization.
• Ohio Personal Privacy Act (OPPA): strict regulations for businesses with respect to collecting, processing, and sharing data, thereby establishing a more secure environment for personal data.
• Ohio Revised Code 1347: Responsibilities of state and local entities in managing personal information systems.
• Federal Trade Commission (FTC) Guidelines: AI and consumer protection.
• Health Insurance Portability and Accountability Act (HIPAA): AI in healthcare data management.
• Children’s Online Privacy Protection Act (COPPA): AI and children’s dataPractical implications for compliance in AI projects

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Session 7: Risk Management in AI (2.5 hours)

• Identifying risks specific to U.S. businesses:
• Data privacy and security.
• Bias and discrimination in AI systems.
• Repetitional and legal risks.
• Discussion of real-world ethical challenges faced by companies using AI (e.g., biased hiring algorithms, privacy violations).
• Developing mitigation strategies aligned with U.S. regulations

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Session 8: Practical Workshop: AI Implementation Roadmap (2 hours)

• Group activity: Develop a strategic AI roadmap for a U.S.-based business scenario.
• Identifying key objectives and milestones.
• Addressing regulatory and ethical considerations.
• Presentation of roadmaps and peer feedback

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Session 9: Group Activity: Compliance Assessment for AI Solutions (2 hours)

• Hands-on exercise: Assess a hypothetical AI solution for regulatory compliance, focusing on privacy and accountability.
• Group presentation of compliance challenges and solutions.

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