AI Governance Now

Exploring How Organizations Can Govern the Growing Use of AI and Agents
Thursday, May 21, 2026 |  1:00 PM ET
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Artificial Intelligence is reshaping how organizations operate at a rapid pace; few technologies have matched. Some organizations are experimenting, while others have embedded AI systems and agents across workflows, products, customer interactions, and decision-making processes.
 
As organizations adopt new technologies to accelerate growth, responsible governance provides guardrails and controls to reduce risk. Yet in the case of AI, governance is not only lagging, it's being overlooked. For security, risk, and compliance leaders, this gap translates into unmanaged risk at scale. The need for responsible AI governance is not optional or aspirational—it's a business requirement.
 
In this webinar, we will explore enterprise AI governance today, where programs succeed or fall short, and best practices for policies, controls, risk management, and oversight. We will provide a strategic approach for cybersecurity and Governance, Risk, and Compliance (GRC) leaders and practitioners, along with their companies, to help establish AI governance as a requirement rather than an afterthought. From strong security posture to regulatory requirements, AI Governance should be a key pillar in every organization, especially in the new age of agentic AI. Join us to learn how your enterprise can successfully implement a strong AI Governance program.
 
Who should attend this webinar?
  • CFOs and Financial Teams
  • CISO and Executive Leadership
  • Compliance and Audit Teams
  • CTOs
  • CIOs
  • Delinea Customers
  • Directors of Information Security
  • Directors of Security & Risk
  • Directors of Security Operations
  • Fastpath Customers
  • Identity and Access Management Teams
  • IT Operations: Systems Administrators, Helpdesk Teams, Infrastructure Management, Workstation Management, etc.
  • IT Security Professionals
  • Legal Advisors
  • PAM and IAM Teams
  • Professionals in Ransomware and Response Strategy
  • Risk Management Professionals
  • StrongDM Customers
What will I learn?
  • What effective AI governance actually looks like in practice
  • How to operationalize AI governance within your existing information security and GRC programs
  • How to reduce AI-driven identity and security risks at scale
Get answers to these important questions:
  • What steps can we take now to implement effective AI governance?
  • Where are organizations failing with AI governance today, and how can we avoid it?
  • How can we align AI governance with cybersecurity and compliance frameworks?
  • Why is securing AI agents and machine identities critical to strong AI Governance?
 

Featured Speakers

Frank Vukovits
Frank Vukovits
Frank is Chief Security Scientist at Delinea. He has over three decades of experience as an auditor and security professional, along with corporate IT executive management. Frank holds Certified Internal Auditor (CIA) and Certified Information System Auditor (CISA) designations, and passed the CISSP exam in 2001. He is a frequent speaker at audit (IIA), IT audit (ISACA), software publishers, security, and user group events.
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Guru Sethupathy, GM of AI Governance, Optro

Guru Sethupathy is the GM of AI Governance at Optro. Previously, he was the founder and CEO of FairNow (now part of Optro), a governance platform that simplifies AI governance through automation and intelligent and precise compliance guidance, helping customers manage risks and build trust and adoption in their AI investments. Prior to founding FairNow, Guru served as an SVP at Capital One, where he led teams in building AI technologies and solutions while managing risk and governance. Guru also spent time at McKinsey, where he advised Fortune 100 leaders on harnessing the power of analytics and AI while managing risks. All told, Guru has spent two decades in the AI space, spanning academia, corporate, and start-up roles, conducting research on AI systems and their implications for business value, risks, and the workforce. He has a BS in Computer Science from Stanford University and a PhD in Economics from Columbia University.