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Course Outline

Foundations of Sovereign AI

  • Understanding what sovereign AI entails for regulated organizations.
  • Business, legal, and operational drivers behind sovereignty.
  • Key control domains: data, models, infrastructure, and operations.

Regulatory Requirements and Risk Mapping

  • Data residency, privacy regulations, and industry-specific obligations.
  • Mapping sensitive data to specific AI use cases.
  • Identifying risks related to cross-border data flows, logging, and third-party exposure.

Governing Data, Prompts, and Logs

  • Prompt governance and defining acceptable use boundaries.
  • Logging policies for prompts, responses, and metadata.
  • Practices for retention, redaction, masking, and access control.
  • Exercise: Conducting an AI data flow review to identify governance gaps.

Model Hosting and Inference Environment Options

  • Evaluating public APIs, private clouds, on-premise, and hybrid deployment models.
  • Key factors in determining optimal model execution locations.
  • Weighing trade-offs between control, security, cost, and operational ownership.

Vendor Dependence and Portability

  • Identifying common lock-in patterns in models, tools, and platforms.
  • Enhancing portability via modular architecture, open interfaces, and clear contractual terms.
  • Exercise: Assessing vendors against sovereignty criteria.

Governance Model and Action Planning

  • Defining roles and responsibilities across IT, security, legal, and compliance functions.
  • Establishing approval workflows for use cases, models, and operational changes.
  • Expectations for auditability, monitoring, and incident response.
  • Constructing a practical sovereign AI roadmap and defining immediate next steps.

Requirements

  • Fundamental knowledge of AI concepts, data governance, and compliance standards.
  • Experience with enterprise technology, cloud infrastructure, security, or risk management decision-making.
  • No programming background is necessary.

Audience

  • IT leaders, enterprise architects, and platform managers.
  • Risk analysts, compliance officers, legal counsel, and data governance professionals.
  • Security teams and business executives responsible for driving AI adoption in regulated sectors.
 7 Hours

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