Udemy - AI Governance for Managers

AI Governance for Managers
https://WebToolTip.com
Published 7/2026

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Language: English | Duration: 1h 9m | Size: 276.31 MB
Govern AI use cases, risks, policies, vendors, oversight, and responsible decisions as a manager.
What you'll learn

Identify what AI governance means in practical management terms and why it matters for business teams.

Distinguish between low-risk, medium-risk, high-risk, and prohibited AI use cases.

Ask the right governance questions before approving, buying, piloting, or scaling an AI-enabled tool.

Recognize major AI risk categories, including data risk, privacy risk, security risk, bias, model behavior, vendor risk, operational risk, and reputational risk

Apply responsible AI principles such as fairness, transparency, explainability, human oversight, reliability, security, and accountability.

Design a practical AI governance operating model using inventories, intake forms, risk tiers, approval workflows, roles, policies, monitoring, and escalation pa

Evaluate vendor and SaaS AI features using practical due diligence questions about data use, model updates, security, documentation, and accountability.

Create a 30-60-90 day roadmap for improving AI governance within a business function or management team.
Requirements

No coding, data science, or machine learning background is required.

Basic business, management, operations, risk, compliance, HR, finance, product, legal, IT, or digital transformation experience will be helpful.

Students should have an interest in how AI is used in real organizations and how managers can govern AI responsibly.

A willingness to think critically about risk, accountability, policies, vendors, data, and decision-making is recommended.