Ai Risks: What Can Go Wrong
Published 5/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 53m | Size: 400.3 MB
Practical guide to AI risks, governance, oversight, and safe business use
What you’ll learn
Identify the main business risks of using AI in practice
Understand how AI can fail in real business situations
Recognise common AI mistakes before they cause damage
Apply practical ways to reduce AI-related risks at work
Requirements
No prior AI or technical knowledge is required. A basic familiarity with workplace tools and business decision-making is enough.
Description
AI can improve productivity, speed, and decision-making. But it can also create costly mistakes, legal issues, reputational damage, and hidden business risks. This course helps you understand how AI fails in practice, why these failures happen, and what organisations can do to manage AI more safely. The course is designed for business professionals, managers, and decision-makers, it focuses on practical, real-world use rather than technical theory or complex compliance frameworks.
You’ll learn how AI can go wrong across real business environments, from flawed outputs and poor decisions to data exposure, operational breakdowns, vendor dependency, and weak accountability. The course explains the most important AI risk areas in business language and shows why AI creates a different kind of risk than traditional software or IT systems.
Through practical examples and real-world cases, you’ll see how AI failures happen, why they are often missed until it’s too late, and what organisations can do to reduce the chance of expensive surprises. You’ll also learn practical approaches to managing AI risks, without needing a technical or compliance background.
If you use AI at work, evaluate AI tools, oversee AI projects, or make decisions about AI adoption, this course will help you approach AI with more clarity, stronger judgment, and better risk awareness.
Who this course is for
Business professionals, managers, and decision-makers who use or oversee AI at work
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