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Practical AI Use in Leadership

Microsoft via Coursera

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Overview

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Practical AI Use in Leadership prepares you to use Microsoft Copilot as a decision support capability while retaining judgment and accountability. Leaders are expected to expand insight responsibly without outsourcing critical thinking. You will practice framing open-ended leadership decisions, interpreting Copilot-generated insights, and evaluating ethical, feasibility, and reputational risks. The course follows the leadership decision lifecycle: frame → interpret → judge → learn. AI is positioned as a capability amplifier—not a substitute for responsibility. You will assess assumptions, articulate trade-offs, and evaluate outcomes in alignment with Microsoft Responsible AI principles. By the end of this course, you will be able to integrate AI-supported insight into leadership workflows responsibly, support structured decision-making, and demonstrate ownership of outcomes in AI-supported environments.

Syllabus

AI-supported decision framing with Copilot

This module develops the ability to frame ambiguous business situations into decision-ready problems and use Microsoft Copilot to explore strategic options. Emphasis is placed on leadership ownership of framing and assumptions, rather than treating Copilot output as an answer.

Interpreting Copilot and data for strategic insight

This module focuses on interpreting Copilot-generated outputs and data summaries and translating them into leadership insight. Learners practice separating signal from noise and constructing narratives that support Microsoft leadership judgment rather than replacing it.

Risk, ethics and judgment in Copilot-supported decisions

This module develops leadership judgment when Copilot recommendations raise ethical, feasibility, or reputational concerns. Learners evaluate Copilot-supported options through Microsoft’s Responsible AI principles and decide when to proceed, adapt, or pause.

Evaluating outcomes and learning from Copilot-supported decisions

This module focuses on evaluating outcomes of Copilot-supported decisions and turning results into learning. Learners practice reviewing variance, refining metrics, and improving future Copilot use in line with Microsoft’s growth mindset.