• What AI governance really means—and why it’s critical to enterprise-scale AI deployment

• Key components of a successful governance framework, including policy, accountability, oversight, and tooling

• How to align governance with regulatory compliance, risk management, and business strategy

• Practical steps for implementing governance across data pipelines, model lifecycles, and stakeholder workflows

• The role of cross-functional collaboration in driving responsible and transparent AI practices

• Common challenges enterprises face when scaling governance—and how to overcome them

• Examples of how leading organizations are building governance into their AI infrastructure from day one

Why This Matters:

As organizations scale AI, the need for strong, standardized governance becomes urgent. Without the right framework, companies risk model failure, regulatory exposure, and reputational damage. This 50-minute technical masterclass will give you a blueprint for designing and deploying enterprise-wide AI governance that balances innovation with control. You’ll walk away with actionable guidance on structuring policies, assigning ownership, and integrating tools to ensure your AI systems are accountable, auditable, and aligned with your organization’s values and goals.

• AI/ML Engineers & Technical Leads implementing governance controls across model pipelines

• Enterprise Architects & Infrastructure Leads designing scalable, compliant AI systems

• Risk, Compliance & Legal Teams shaping responsible AI policy and oversight

• Data Governance and MLOps Professionals building cross-functional systems of control

• Technical Executives & CIOs overseeing AI transformation and organizational accountability