I took the CET exam last month and came in at 64%, just below the 70% passing mark. I work in enterprise IT with about 8 years across cloud and data infrastructure, so the technical foundations section was fine — I probably scored close to 85% there. It's the AI governance and ethics portion where I lost most of my points.
I'd been studying for 5 weeks, averaging 1 hour a day on weekdays. Looking back at what I remember, the questions weren't asking me to define terms — they were presenting organizational scenarios and asking what the right governance approach would be. That's a very different skill from knowing the NIST AI RMF framework in theory.
Has anyone found specific resources that prepare you well for the scenario-based ethics questions? I've gone through the IAMCP study materials and a lot of it feels too surface-level for how the actual exam tests this content. Retake is 6 weeks out.
64% with strong technical scores means you're close. If the ethics section is roughly 25–30% of the exam, bringing it from failing to passing would put your total well above 70%. The NIST AI RMF Playbook has scenario examples in the appendices that are much better practice than the IAMCP materials.
I passed on my first attempt but I work in AI policy so ethics was my strong section. What I noticed is that the exam heavily favors responses involving stakeholder consultation and iterative review over one-time assessments. If a question asks what to do first, 'consult stakeholders' is almost always right.
Six weeks is plenty of time. I'd spend the first two weeks on AI governance frameworks specifically — the EU AI Act risk tiers show up in ways the IAMCP materials don't cover well. Then use weeks 3–6 for scenario practice using real-world case studies.
The scenario-based ethics questions are the hardest part for technical people — we're used to there being a correct answer rather than a 'most appropriate' one. Reading through AI ethics case studies from organizations like the Partnership on AI helped me more than any formal study guide. Real-world examples train the judgment the exam is actually testing.
I was in almost the exact same spot after my first attempt — solid on the technical side, completely blindsided by how deep they went on governance frameworks. What I changed was stopping trying to learn AI ethics conceptually and instead drilling actual scenario questions. I spent two weeks on free cet integration and implementation practice questions and that shifted my thinking from "what is responsible AI" to "what does a governance officer actually do when X happens." That distinction matters more than I expected.
Second time I passed with a 76%. The governance section still wasn't easy but I wasn't guessing anymore. If you've got the technical background you're probably fine there, so don't waste time reviewing what you already know. Put your hours into the policy and oversight scenarios, especially anything around accountability structures and bias mitigation procedures.
Honestly I almost just rescheduled and kept pushing it off because the AI governance stuff felt like memorizing policy documents for a job I don't actually do. I'm a cloud infrastructure guy, I didn't care about ethics frameworks, and it showed when I first started studying. What helped was stopping trying to understand it and just accepting that the CET wants you to know specific frameworks by name and what layer of the stack they apply to. Annoying but it's not that deep once you accept it.
I passed on my second attempt with a 73% and governance was still my weakest section. Don't overthink it. If you've got the technical side locked down you're not as far off as you think, you just need enough governance points to stop bleeding. Grind the practice questions specifically for that section until the patterns click. They reuse the same conceptual angles a lot.
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