EXIN BCS Gen AI Award study guide
EXIN BCS Gen AI Award · Work through your exam, one topic at a time.
The EXIN BCS Gen AI Award is a vendor-neutral certification covering generative AI, offered under the EXIN and BCS names. This page is an independent study resource and is not affiliated with, endorsed by, or sponsored by EXIN or BCS. Because the official certification page was unreachable when this page was last checked, exam logistics such as question count, duration, passing score, fee, retake rules and certificate validity are not published here; confirm them with the awarding body before booking. Preparation should follow the four published domains, which carry equal weight: generative AI fundamentals, capabilities and limitations; prompt design and effective use of generative AI tools; ethical, legal and security considerations; and business application and value. The EXIN BCS Gen AI Award study guide has 4 sections and about 2,360 words.
01Generative AI Fundamentals
Domain 1 tests whether you can explain, in mechanism terms, how generative AI produces an answer - and therefore why it behaves as it does. Expect vocabulary questions on tokens, embeddings, transformers, training stages and sampling settings, plus scenario questions that ask you to predict model behaviour.
476 words, about 2 min02Capabilities and Limitations of Generative AI
Domain 2 tests judgement: can you decide whether generative AI is the right tool for a specific task, and what safeguards that task needs? Questions pair a plausible-sounding claim with a scenario and ask you to spot the limitation.
464 words, about 2 min03Prompt Design and Effective Use of Generative AI Tools
Domain 3 tests practical prompt engineering: can you turn a vague request into a specification a model can follow, and can you explain why one prompt outperforms another? Questions typically show two versions and ask which change improves reliability, or ask for the control that prevents a specific failure.
447 words, about 2 min04Ethical, Legal and Security Considerations of Generative AI
Domain 4 tests risk spotting and control selection: data protection, intellectual property, transparency, fairness, and the security threats specific to LLM applications. Scenario questions ask what you must do before deployment, or which control addresses a named threat.
973 words, about 5 min