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The IAPP Artificial Intelligence Governance Professional credential is a 100-question, 180-minute linear exam covering four domains. Roughly thirty percent of items are scenario-based. The current Body of Knowledge, v2.1, was released February 2, 2026 and adds emphasis on agentic architectures, third-party risk management, and strengthened data governance.
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A multinational SaaS vendor based in Toronto is launching a customer-support chatbot for EU-resident end users. The product team wants to use a third-party foundation model accessed through an API and fine-tune it on six months of historical support tickets. Legal has flagged that the chatbot may qualify as a high-risk AI system under the EU AI Act because of how it handles complaints, while privacy counsel is asking which obligations attach to the fine-tuning data.
Which combination of obligations is most likely to apply before the chatbot is placed on the EU market?
- Article 30 records of processing on the support tickets, an EU AI Act conformity assessment, and a DPIA covering the fine-tuning.
- An EU AI Act conformity assessment, with the foundation model provider's diligence covering downstream GDPR controller duties on the deployer's behalf.
- GDPR breach notification procedures and an algorithmic impact assessment under Canada's AIDA, applied because the vendor is headquartered in Toronto.
- A data protection impact assessment, since complaint-handling chatbots fall outside the EU AI Act's high-risk classification by default.
Show explanation
The correct answer combines three independent obligations that all attach in this scenario. EU controllers and processors must maintain Article 30 records of processing whenever they handle personal data, and historical support tickets qualify. The EU AI Act's conformity assessment requirement is triggered before a high-risk AI system is placed on the EU market — and a chatbot used to evaluate or route complaints in a regulated service is a candidate for high-risk classification on a fact-specific basis, not categorically excluded. Fine-tuning a foundation model on personal data is a new processing purpose that, given the volume and automated context here, meets the GDPR threshold for a DPIA.
The other choices each fail on one fact. A foundation-model provider's own diligence does not discharge a deployer's GDPR controller duties — the deployer remains the controller for its own processing. Canada's AIDA had not yet come into force as of the BoK v2.1 timeframe, and the operative trigger here is EU market placement, not the vendor's incorporation. And chatbots are not categorically excluded from high-risk classification — transparency obligations apply universally, and high-risk status is fact-specific.
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