Operationalizing AI for Business Impact

This unit teaches how to move from AI concepts to practical, ethical, and governed deployment across organizations. Students will learn operating models, required technical capabilities (CV, NLP, LLMs), responsible AI practices, team design, prompt engineering, opportunity mapping, and methods to evaluate business impact and regulatory risk.

Learning Objectives

• Analyze AI target operating models, technical capabilities (including unimodal CV/NLP and transformer-based LLMs), and ecosystem configurations to identify and categorize high-value business opportunities
• Apply responsible AI principles, risk transparency practices, and regulatory checklists to design governance, mitigation strategies, and compliance plans for proposed AI initiatives
• Demonstrate prompt engineering, model selection, and integration techniques (e.g., Gemini, ChatGPT, Ernie) within the product design cycle and new team formations to operationalize AI solutions
• Evaluate business impact, implementation ease, and ethical implications to prioritize AI projects and produce an actionable AI opportunity map and deployment roadmap