AI Governance in Practice: Operationalizing Governance for Enterprise AI
Webinar Speaker: David Loshin, President of Knowledge Integrity
Date: Wednesday, April 30, 2025
Time: 12:00 p.m. PT / 3:00 p.m. ET
Organizations are rapidly learning about the myriad benefits of adopting maturing artificial intelligence (AI) capabilities. However, integrating AI into the enterprise carries with it vulnerabilities that can lead to negative outcomes, such as leaking sensitive information, producing unfair or harmful responses, and regulatory non-compliance, not to mention impaired decision-making due to model confabulation/hallucination or automation bias.
AI standards must be established for input quality, access control, and trustworthiness. Ensuring adherence to those standards requires dedicated governance tactics to be applied consistently across the end-to-end life cycle—from data preparation and self-service analytics to machine learning and generative AI applications or projects.
Organizations need to develop a framework that enables transparency and accountability around AI models, while they use the right tools and infrastructure to maintain visibility into AI governance to reduce risk across the corporate AI portfolio. In this webinar, we explore the issues associated with operationalizing enterprise AI governance. Topics include:
- Centralizing AI oversight over end-to-end workflows and processes
- Maintaining an accurate and up-to-date lineage for AI workflows
- Instituting methods for traceability, transparency, and explainability of AI/ML models
- Operationalizing data protection and access controls
- Instituting quality controls over the information used to build, train, and fine-tune AI models
- Fully integrating and embedding governance policy compliance to protect against negative AI outcomes (e.g., noncompliance, data leakage, harmful content, inherent bias)
Date: April 30, 2025
Time: 12:00 pm PT
David Loshin