AI Governance, Risk & Assurance

Artificial intelligence is increasingly embedded in business decisions, customer interactions, operational processes, analytics, and employee workflows. As AI adoption expands, organizations need to understand not only what these systems can deliver, but also who is accountable for their use, what risks they introduce, how human oversight should operate, and whether existing controls remain effective as AI systems and their operating environments change.
 

Boost Consulting & Training offers this course to develop practical capability for governing and assuring organizational AI. Participants learn to identify and classify AI use cases, assign accountability, assess risks across the AI lifecycle, establish proportionate controls, address third-party and generative AI exposure, monitor AI performance and incidents, and determine what evidence is needed to provide meaningful assurance. The course approaches AI from a governance and risk perspective rather than from technical model development.
 

The main concept of this course is to create accountable and controlled AI use by connecting each AI application with clear ownership, understanding risks, effective controls, ongoing monitoring, and evidence-based assurance.

• Identify organizational AI use cases requiring governance and oversight.
• Classify AI applications according to their purpose, impact, and risk significance.
• Establish clear accountability and human oversight for AI-enabled activities.
• Assess data, model, operational, behavioral, and third-party AI risks.
• Design proportionate controls across the AI lifecycle.
• Establish monitoring and escalation for changing AI performance and risk.
• Evaluate evidence required to provide assurance over AI governance and controls.
• Develop an integrated governance and assurance approach for organizational AI.