From the course: CompTIA SecAI+ (CY0-001) Cert Prep
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Corporate AI policies
From the course: CompTIA SecAI+ (CY0-001) Cert Prep
Corporate AI policies
Legal frameworks set the floor, but day-to-day compliance lives in the corporate policies that guide employees, contractors, and partners. As we've discussed, good policies turn high-level principles into clear instructions about which tools are allowed, how data may flow, and when extra review is required. They also create a single source of truth that security, procurement, and product teams can reference when questions arise. Every organization should publish an allowed list of AI services that have passed security and privacy review, and a not allowed list for anything that fails the review or has yet to be assessed. Employees must understand that using an unsanctioned chatbot, code assistant, or analytic API, even for a quick experiment, can expose confidential data, violate license terms, or create untracked models that slip past governance controls. The policy should describe an intake process for new tools, the evidence required for approval, and the consequences of bypassing…
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Contents
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The AI lifecycle1m 39s
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Business alignment in the AI lifecycle1m 43s
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Data collection2m 20s
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Data preparation3m 15s
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Model development and selection2m 13s
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Model evaluation and validation2m 29s
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Model deployment and integration3m 25s
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Monitoring and maintenance3m 19s
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Manipulating application integrations4m 8s
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AI supply chain attacks2m 4s
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Insecure plug-in design2m 9s
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Insecure output handling1m 23s
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Output integrity attacks2m 8s
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Model denial of service1m 31s
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Excessive agency1m 33s
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Overreliance1m 34s
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AI hallucinations1m 4s
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Monitoring prompts and responses2m 51s
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Log monitoring4m 30s
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Rate and cost monitoring5m 1s
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Auditing for AI hallucinations3m 33s
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Auditing for accuracy3m 29s
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Auditing for bias and fairness4m 35s
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Auditing access and security compliance3m 48s
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Responsible AI5m 29s
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AI risks2m 23s
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Introduction of bias2m 37s
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Accidental data leakage2m 53s
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Reputational loss2m 11s
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Accuracy and performance of the model2m 22s
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Intellectual property risks3m 31s
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Autonomous systems2m 27s
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Shadow IT and shadow AI1m 48s
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Awareness training2m 21s
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