• Evaluate the strategic value of AI functionalities such as chatbots, reasoning, and multimedia.
• Construct an evaluation of the cost of an AI system.
• Distinguish between major AI model types and terminology.

• Explain the most relevant AI platform or approach for a specific sector and its application to agentic AI use cases.
• Evaluate the key factors influencing the selection of open-source versus proprietary AI platforms within a specific organizational context.
• Develop a landing page using AI.
• Prompt AI to create a visual mock-up and functional HTML code.
• Activate the code by saving and reuploading it.
• Explain a new AI workflow within an organization.

• Construct a use case demonstrating agent-based interaction across integrated tools.
• Write a structured email-style proposal that outlines a specific use case for an AI agent within an organizational context.
• Analyze a business workflow to determine how an AI agent could improve efficiency, reduce costs, or enhance user experience.
• Design an integration approach that specifies how the proposed agent would connect with existing systems, platforms, or application programming interfaces (APIs).
• Evaluate the potential risks, ethical considerations, and success metrics associated with deploying the proposed AI agent.

• Analyze organizational AI systems and workflows to identify potential cybersecurity risks using the National Institute of Standards and Technology (NIST) Cybersecurity Framework categories.
• Evaluate current security practices to identify gaps in access control, monitoring, response, and recovery capabilities.
• Develop a structured AI risk and security plan, including stakeholders, training, and incident response procedures.
• Recommend actions to improve organizational readiness across identify, protect, detect, respond, and recover domains.
• Analyze organizational AI systems and workflows to identify potential cybersecurity risks.
• Evaluate how accountability is defined and enforced alongside security practices and governance in AI systems.

• Describe the organizational context, including industry, organization type, and department, relevant to a proposed AI-driven product design initiative.
• Summarize the current product design workflow within an organization to establish a baseline for improvement.
• Select an appropriate AI technology for integration into a product design process based on its capabilities and relevance.
• Develop a structured plan outlining how AI can be integrated into a product design workflow to improve efficiency, effectiveness, or quality.
• Identify an appropriate AI agent architecture for a given organizational context and explain key trade-offs.
• Identify opportunities for AI-enabled BPO and describe their potential organizational impact.

• Propose measurable key performance indicators (KPIs) that evaluate the effectiveness of an AI sstem in relation to business outcomes.
• Describe the organizational context, including sector, organization type, and department, relevant to an AI implementation.
• Summarize the purpose and functionality of a proposed AI system within a business workflow.
• Write three to five key performance indicators (KPIs) that measure the effectiveness of an AI implementation.
• Evaluate how the selected KPIs align with business goals and indicate whether the AI system is achieving its intended outcomes.

• Identify applicable regulatory frameworks (e.g., GDPR, CCPA, HIPAA) relevant to a specific AI use case.
• Analyze the risks associated with deploying AI systems, including both compliance and operational risks.
• Apply appropriate testing strategies (e.g., sandboxing, A/B testing, safety checks) to evaluate AI system behavior.
• Develop a comprehensive AI governance plan that integrates regulations, testing, risk mitigation, and documentation practices.
• Create guiding questions that identify key regulatory and implementation considerations in real-world AI healthcare scenarios.
• Classify AI use cases using the Risk–Speed Quadrant Framework.

• Explain how AI can be strategically integrated into organizational functions to create business value.
• Evaluate the suitability of AI technologies for specific organizational use cases.
• Analyze the cost, security, and operational implications of AI adoption.
• Assess the human and organizational factors that influence successful AI implementation.
• Synthesize course concepts into a structured approach for organizational AI adoption.
• Evaluate ethical risks in a proposed AI system by identifying a potential issue, assessing its business impact, and recommending an appropriate mitigation strategy.

In this course, apply your learning in a final capstone project designed to demonstrate real-world impact. Choose between two strategic paths:

• Design a comprehensive AI integration plan tailored to a specific business function
• Develop an executive presentation that outlines a transformative, agent-based AI initiative.

Support your project with a detailed risk-benefit analysis, cost implications, and measurable KPIs to demonstrate strategic value.