AI Governance: Risk, Ethics and Responsible Adoption [EN]

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.