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AIB-C01 · Sample questions
10 real questions from the CertifyDeck AIB-C01 bank, spread across the domains of the official AWS Certified AI Business Strategist skills outline, with the correct answer and a full explanation of why the other options are wrong. They are original questions written from the public syllabus, not exam dumps, and they are the same style you will find in the practice tests and mock exams.
Correct answer: A. As a rule-based AI technique that is not ML, because the system does not learn from data.
AWS lists rule-based systems among the methods in the field of AI, alongside ML itself, while ML is defined by learning patterns from data to perform tasks without explicit instructions. Processing high volumes automatically does not make a system ML when the decisions come from hand-written rules. Generative AI creates new content, and deep learning uses neural networks, not layers of rules.
Correct answer: A. Align terminology with global standards such as ISO/IEC 23053 and ISO/IEC 42001 as a shared framework.
AWS groups ISO/IEC 23053 and ISO/IEC 42001 under global frameworks and a unified AI vocabulary, and explains that technical standards such as ISO/IEC 42001 provide a common framework that fosters trust and interoperability across a global landscape. Adopting one vendor's terms is tempting for speed, but a vendor's vocabulary is not an international standard and ties the company to that vendor. Separate local glossaries keep the confusion, and postponing a shared vocabulary leaves partners and auditors confused during deployment.
Correct answer: A. Place the question after the report text, at the end of the prompt.
AWS guidance for prompt design is to place the question or instruction at the end of the prompt, because including the task at the end helps the model determine which information it has to find in the supplied text. Removing the report discards the input the answer depends on, and repeating it only adds length without clarifying the task.
Correct answer: A. Define separate author, approver and publisher roles for every model release.
The CAF-AI security perspective recommends establishing roles and responsibilities for creating and training models, including an author, approver and publisher approach to model release. More tests by the same person still leave one individual accountable for every step, with no independent approval. A request from the business unit or a vendor's sign-off does not create internal accountability for what is released.
Correct answer: A. Define who approves data sources and AI use, weighing data sensitivity and lawful use.
The CAF-AI security perspective says to establish who can approve data sources and the use of AI, considering data classification or sensitivity, regulated data, provenance and the lawful right to process the data. Letting each team decide keeps the accountability gap, because keeping data internal says nothing about whether its use is approved or lawful. Automatic approval and complaint-driven reviews also leave no one accountable before the data is used.
Correct answer: B. Production-grade deployment pipelines, governance, observability and an incident response process.
To move from Experiment to Launch, AWS recommends production-grade infrastructure with CI/CD and standardized deployment, production-grade governance, observability adapted to generative AI and operational excellence through incident response and SLAs. Awareness workshops and more PoCs repeat earlier levels, and a marketplace of reusable components is a later step for scaling, not the pathway to the first production launches.
Correct answer: C. Publish the data products in a shared catalog with clear owners, documentation and governed access.
The AWS CAF-AI data curation capability recommends making data discoverable through human-readable catalogs and dictionaries, with direct dataset owners or data stewards, so that teams of all skill levels can find and reuse data and shadow data operations are avoided. A single team that copies every dataset by hand becomes a bottleneck that slows AI work. Opening all data to everyone ignores the access controls that governed sharing requires, and waiting for a complete enterprise model blocks value indefinitely.
Correct answer: C. Build an evaluation dataset with validated ground truths and agree on success criteria up front.
AWS guidance says the quality of an evaluation depends on a high-quality evaluation dataset compared against verified ground truth, and its model migration guidance says the data, evaluation criteria and success criteria should be defined at the start so stakeholders can sign off with confidence. Switching all traffic first puts the business at risk before anything is measured, generic vendor benchmarks do not measure this company's use case, and defining criteria after seeing results removes an objective sign-off.
Correct answer: C. Plan the budget by lifecycle phase and forecast it from business drivers such as volume.
AWS CAF-AI describes AI costs as a zigzag of low and high phases across data preparation, PoC, and MVP, which must be planned in advance when budgeting, and the Well-Architected Framework recommends dynamic budgets based on trends or business drivers. A flat budget at the PoC run rate is tempting because it is simple, but it ignores that later phases can cost much more; deferring the budget removes planning altogether.
Correct answer: A. Product, because the initiative creates a new value proposition and revenue model.
The AWS CAF-AI describes four transformation domains, and the Product domain is about reimagining the business model by creating new value propositions and revenue models that capitalize on AI. A usage-based policy sold by subscription is a new offer and a new way of earning revenue. The Process domain is tempting, but it covers digitizing and optimizing existing operations, not creating a new product or revenue model.
Answer each question before opening the explanation, and write down why you discarded the other options. On AIB-C01, most mistakes come from choosing an option that is technically possible but does not meet every requirement in the scenario.
These 10 questions are a taste of the format, not a diagnostic. To know which domains you fail, practice by domain for free and take a timed mock exam that mirrors the official weights and duration.
Start for free, no sign-up or card. Every question includes an explanation like the ones above, and the mock exam reproduces the official AIB-C01 format.