Topic: AI Governance Challenge: Data Leakage, Model Risk, Third-Party & Shadow AI
Abstract: AI risks rarely emerge in controlled environments. Instead, they surface through shadow AI, rapid experimentation, and ungoverned use of third-party tools, leading to data leaks, bias, compliance failures, and operational instability.
This session takes a real-world, use-case-driven lens to AI risk. We’ll break down how risks manifest across the AI lifecycle—from unauthorized adoption and data exposure to model drift and vendor dependencies. You’ll also learn how to identify and prioritize AI use cases based on risk exposure and business value, while embedding governance at every stage—from ideation to deployment and monitoring.
Gain practical strategies to identify, assess, and control AI risks in dynamic environments, while safely scaling AI adoption and maintaining trust.
Key Takeaways:
- Detect and mitigate shadow AI and unauthorized usage
- Understand and manage data leakage and privacy risks
- Address model risk, bias, and lifecycle challenges
- Evaluate and govern third-party AI vendors and ecosystems
- Prioritize AI initiatives based on risk vs. business impact
Speaker:
Bennie Cleveland, vCISO, VanRein Compliance
Bio: Bennie Cleveland is a seasoned cybersecurity executive and enterprise risk strategist with more than 20 years of experience leading cybersecurity, compliance, incident response, disaster recovery, AI governance, and resilience programs across financial services, healthcare, life sciences, SaaS, higher education, insurance, retail, and technology sectors.
In his current role at VanRein Compliance, Bennie serves as a vCISO, cybersecurity advisor, and auditor, bringing hands-on leadership across cybersecurity governance, disaster recovery, incident response, penetration testing, audit readiness, and regulatory compliance. He helps organizations strengthen their security posture by assessing risk, validating controls, identifying vulnerabilities, improving resilience, and aligning security programs with frameworks such as NIST, HIPAA, HITRUST, SOC 2, ISO 27001, and industry best practices. Bennie brings both strategic executive guidance and practical execution, helping clients move from compliance gaps and security uncertainty to measurable risk reduction, audit readiness, and operational resilience. He helps organizations assess risk, strengthen security posture, validate technical controls, prepare for audits, and align cybersecurity programs with business objectives, regulatory requirements, and operational resilience goals.
His work spans leading frameworks and standards, including NIST AI RMF, ISO/IEC 42001, NIST CSF, HIPAA, HITRUST, ISO 27001, SOC 2, GDPR, and related governance requirements. Bennie focuses on translating technical, operational, and AI-driven risk into practical business controls, executive decision-making, and audit-ready evidence.
Bennie holds a broad portfolio of credentials, including but not limited to CCISO, CISM, CISA, CRISC, CGEIT, CHFI, CEH, PMP, EDRP, AAIA, AIGP, and CIPM, reflecting his depth across cybersecurity leadership, governance, risk, compliance, audit, penetration testing, incident response, disaster recovery, privacy, and emerging AI audit practices. He is known for bridging strategy and execution by helping organizations move from reactive compliance to proactive, measurable cyber and AI governance programs.
