AI Governance

Practices and safeguards to deliver secure, responsible, and manageable Generative AI systems in production.

Rolling out an AI system without good governance can be really ugly. Data leaks. Biased output. Runaway costs. Poor legal compliance. Privacy exposures. Every company putting AI into production faces these very real risks. AI Governance is a one-of-a-kind playbook that translates abstract governance theory into the concrete practices you need for safe, responsible AI.

In AI Governance, you’ll learn how to:

• Match the right safeguards to your deployment model
• Apply a framework that transforms governance from paperwork into workflow
• Catch problems like prompt injection, bias, and data leakage early
• Adapt to AI laws and standards with defensible, scope-aware controls
• Operationalize ethics into testing and oversight for trustworthy outcomes

The massive training datasets and generalized knowledge that make LLMs like GPT, Gemini, DeepSeek, and Claude so impressive can be a challenge to govern in a production business environment. You want your chatbot to be smart and friendly, but you need to be certain its responses are accurate and relevant. You want to create personalized customer experiences, but you don’t want to leak PPI. You want to move fast, but without running afoul of rapidly-changing legal requirements. Establishing a solid plan for Governance, Risk, and Compliance (GRC) in Generative AI projects from the beginning will ensure you reap the benefits of AI without risking the core values of your business.