AI for Executives

Abstract

This course will equip participants with the knowledge and insight to shape the AI-driven future of their company. It focuses on how AI algorithms create value for businesses and on the capabilities non-AI companies need to build to organically deploy AI. While building the skills to drive AI Transformation, participants will draft an AI strategy aligned with their organisation’s business context.

Objective

Focus 1 – Data Science and Technological aspects of AI: • Understand the most widely used classes of predictive algorithms, and which of your company’s business challenges they could possibly solve • Understand the technologies, processes and organization required to manage the data that feeds these algorithms, and identify where your company has data maturity gaps • Understand how to develop and operate AI business applications Focus 2 – AI Strategy • Understand the different business models that companies can apply to create economic value with AI, and identify those that are suitable to your company’s context and market • Understand the business environment implications of putting data & AI at the core of an organization’s strategy, then map the data ecosystem(s) and data partnerships relevant to your company • Articulate a coherent AI strategy for your company, including value drivers and a roadmap for use cases deployment and capabilities build-up Focus 3 – Enterprise AI (Operational Capabilities) • Ideate and prioritize AI use cases for your company using a systematic cost-impact assessment framework • Build AI/Machine Learning skills and teams in your organization • Spread AI innovation and value realization across your company’s organization, including operational, commercial, and business functions • Establish values and processes for the ethical and secure handling of data and AI

Content

After demystifying Artificial Intelligence and reviewing the fundamentals of data science and machine learning, the course turns to the application of AI to business organizations. Successive learning modules and case studies follow the journey of MoneyPump, a fictive, mid-sized industrial manufacturer, that transforms itself step-by-step into a data-driven, AI-first company. Each learning module is accompanied by a hands-on assignment during which students apply what they have just learned in the context of their own company. For example, after studying how MoneyPump defined and prioritized its AI use cases, students will produce a shortlist of uses cases for their own company. After learning how MoneyPump resolved the challenge of integrating AI innovation in its existing product management and R&D processes, students will work out an AI innovation framework for their own company etc. Towards the end of the course, each student will piece together the action items defined throughout the different modules into an overall AI strategy and actionable implementation roadmap specific to their company. This project outcome will serve as a basis for the students’ grading. Throughout the program, students will learn how to use AI to create business impact. They will acquire a methodological toolkit to address the business, process and organizational challenges of AI enterprise transformation. Students will also draft an AI strategy for their own company.

Resources