AI for Managers

Module 1

AI foundations for business

Develop a practical understanding of AI concepts and technologies commonly used in business environments. This module introduces the main categories of AI solutions and provides a framework for evaluating where different approaches are most applicable.

• Define key AI concepts, including AI, machine learning, NLP, LLMs, computer vision, OCR, automation, agents, and assistants
• Distinguish between supervised, unsupervised, and reinforcement learning using business-relevant examples
• Differentiate between common types of AI solutions and identify their typical applications
• Evaluate which category of AI solution is most appropriate for a specific business problem

Research existing AI solutions for a selected business problem and document findings by solution category.

Module 2

Identifying AI opportunities

Learn how to identify business challenges that may benefit from AI and assess their potential value. This module focuses on moving from observations and pain points to clearly defined opportunities for AI application.

• Identify AI opportunities relevant to your industry, function, or business area
• Analyze operational challenges and uncover areas where AI could support improvement
• Formulate a business problem that can be addressed through an AI use case

Develop an initial AI Project Opportunity Brief that documents researched pain points and defines one priority business problem.

Module 3

Scoping AI projects

Translate a promising AI opportunity into a well-defined project scope. This module explores solution design considerations, business impact, success metrics, and the trade-offs involved in selecting the right implementation approach.

• Develop and justify a hypothesis for an AI solution based on business needs
• Define relevant ROI measures and key performance indicators for an AI initiative
• Compare build, buy, and fine-tune approaches in the context of a specific project
• Assess organizational factors that influence implementation decisions

Create a research log comparing build and buy options in your field and refine your Opportunity Brief with ROI, KPI, and implementation considerations.

Module 4

Responsible AI

Explore the governance, risk, and compliance considerations that shape successful AI initiatives. This module examines the responsibilities involved in deploying AI and provides a practical framework for identifying and addressing common risks.

• Recognize common governance challenges that can affect AI projects
• Identify data security, privacy, and ethical risks associated with AI solutions
• Assess how governance considerations influence project planning and implementation
• Propose mitigation strategies for common AI-related risks

Expand your AI Project Opportunity Brief by incorporating governance considerations, data requirements, and risk mitigation measures.

Module 5

From plan to proposal

Bring together the business, technical, and governance components of your AI initiative into a clear project proposal. This module focuses on communicating recommendations effectively and preparing for adoption within the organization.

• Describe the key stages involved in deploying and managing an AI solution
• Identify common adoption challenges and the roles involved in implementation
• Define an approach for monitoring performance and measuring ongoing success
• Structure and present a clear AI project proposal tailored to decision-makers

Capstone Project: Develop a complete AI Project Proposal that integrates the opportunity assessment, business case, ROI and KPI framework, implementation approach, governance considerations, and solution monitoring plan.