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Keep shoppingAI Governance: Risk, Ethics and Responsible Adoption
463 students
AI Governance: Risk, Ethics and Responsible Adoption
ai governance | responsible ai | ai ethics and bias | ai risk management | iso 31000 | ai audit | ai adoption strategy
Last updated 9/2026
English
English [Auto],
What you'll learn
- Decide who in a company actually owns AI, and where that role should sit
- Prioritise AI initiatives by impact, feasibility and risk rather than by enthusiasm
- Recognise what AI is genuinely doing across functions, so governance has a subject
- Build a risk heat map and apply ISO 31000 to an AI portfolio
- Apply the three lines of defence model to systems that make decisions about people
- Spot where bias enters an automated decision and what to do about it
- Audit an AI-enabled process: levels, checklist, data collection, gap analysis
- Write the report and the return calculation that keeps governance funded
- Learn alongside Mike's 1.6 million students from 185 countries
- Get the author's experience from Preply, Wargaming, iDeals and Alfa-Bank
Explore related topics
Course content
13 sections • 38 lectures • 18h 23m total length
Requirements
- Responsibility for AI adoption, or for the risk it creates
- No technical background required. Nothing here requires writing code
- Access to whatever AI tools your organisation already uses, officially or not
- English at intermediate level or above, since all lessons are in English
- Willingness to find out how many AI tools are already in use without approval
Description
This course contains the use of artificial intelligence.
Most companies adopted AI before deciding who was accountable for what it does. The tools arrived department by department, and the policy is still a paragraph somebody drafted after an incident.
Why governance written first never sticks
Because it is written by people who cannot say concretely what the systems do. A policy that says "AI use must be ethical and human-supervised" survives one meeting and stops nothing, since nobody knows which decisions are already automated, which model produced them, or who would notice if the output drifted. Governance has to start from an inventory of what is actually running, and almost nobody builds one.
What this course actually covers
Five blocks, from the subject to the framework. First, ownership and strategy: who is accountable for AI in a company, how that differs from the technology roles, when AI is worth doing and when it is not, how to prioritise initiatives by impact, feasibility and risk, and one lesson devoted to risk, ethics, return and the principles of accountability. Second, twelve lessons on what AI is actually doing across a business — screening, onboarding, performance assessment, reward decisions, predictive analytics — because governance without that layer stays abstract. Third, the risk framework itself: the heat map, the fraud triangle, ISO 31000, the risk hierarchy, top-management risk, risk culture and the three lines of defence, ending with personal accountability. Fourth, bias and fairness — how discrimination operates unnoticed, which is precisely what a model reproduces at scale. Fifth, the audit: three levels, the checklist, four data collection methods, gap analysis, the responsibility matrix and the report with a return calculation.
A note on scope and on examples
Twenty-five of the thirty-seven lessons use people-related systems as their material: automated screening, attrition prediction, performance assessment. That is deliberate. Decisions about people are where AI met real consequences first, so that is where the practice and the scrutiny actually exist. The apparatus is domain-neutral — ISO 31000, the three lines of defence, a risk heat map, an audit checklist and a responsibility matrix work on any system. This course does not cover the EU AI Act or other specific legislation; it covers the governance you build regardless of jurisdiction.
Who is teaching this
I am Mike Pritula. I built the people system at Preply as it became a unicorn, and I have worked at Wargaming, iDeals and Alfa-Bank. More than 1.6 million students have enrolled in my courses across 185 countries, and over 150,000 specialists have gone through my programmes. I hold PHRi and SHRM-CP certifications and represent HRCI in more than ten countries.
What is included
Lifetime access to all 37 lessons
Active instructor support in the Q&A section
A Udemy Certificate of Completion
Working material: initiative prioritisation, the risk heat map, ISO 31000, the three lines of defence, the audit checklist and levels, the responsibility matrix, the return calculation
A realistic inventory of what AI is already doing inside an organisation
Where to start
List every AI tool anyone in your company uses, including the ones nobody approved. That list is the actual scope of your governance problem, and it is almost always longer than the policy assumes. Enrol now and start today.
Who this course is for:
- Executives who have been asked to own AI and are not sure what that means
- Risk, compliance and audit specialists facing AI systems for the first time
- Operations and technology leaders adopting AI across several functions
- People and legal professionals responsible for automated decisions about employees
- Consultants advising on AI adoption who need the risk side as well as the upside
- Founders deciding what to automate and what must stay with a person
- Anyone whose company adopted AI quickly and has no policy for it