What Happens When AI Adoption Outpaces Governance
Your employees are already using AI. Your vendors are embedding it into their products. Your leadership team wants to move faster with it. And increasingly, customers, auditors, and regulators want to know how you're managing the risk.
The problem is that most security and compliance programs weren't built for AI.
Join Echelon Risk + Cyber and Vanta for a practical conversation about what happens when AI adoption outpaces governance and what security and risk leaders can do about it.
What You'll Learn in This Webinar
- Where AI creates new blind spots in otherwise mature security and compliance programs
- What ISO 42001 and NIST AI RMF actually mean in practice for your existing controls and governance
- How to move from "we have a framework" to "we can prove it's working" through continuous monitoring, evidence, and expert-led risk management
Meet Your Speakers
Connor Snyder, Governance, Risk, and Compliance Expert, Vanta
Josh Fleming, Senior Cybersecurity Manager, Echelon Risk + Cyber
Webinar Details
- Date: November 18, 2026
- Time: 1:00 PM EST
- Cost: complimentary
- Hosted by: Echelon Risk + Cyber and Vanta
FAQs
Why aren't most security and compliance programs built for AI?
Most programs were designed around systems the organization buys, builds, and controls. AI adds tools employees adopt on their own, features vendors embed into existing products, and data flows that don't appear in traditional asset inventories. As a result, mature programs can have blind spots around who is using AI, for what, and with what data.
What is ISO 42001?
ISO/IEC 42001 is the international standard for an AI management system. It sets requirements for how an organization governs, manages, and improves its use of AI, including roles and ownership, risk assessment, controls, and ongoing review. Organizations can be audited against it for certification.
What is the NIST AI Risk Management Framework?
The NIST AI Risk Management Framework (AI RMF) is a voluntary framework from the U.S. National Institute of Standards and Technology for managing AI risk. It is organized around four functions: Govern, Map, Measure, and Manage. It is a framework to align to rather than a certification.
What is the difference between ISO 42001 and the NIST AI RMF?
ISO 42001 is a certifiable management system standard with auditable requirements. The NIST AI RMF is a flexible, risk-based framework that describes outcomes and practices without a certification. Many organizations use them together: NIST AI RMF to structure how they think about AI risk, and ISO 42001 to formalize and demonstrate their governance.
How do you identify AI use and ownership across an organization?
Start with discovery: which AI tools employees use, which vendors have added AI features, and which internal teams are building or integrating AI. Then assign an accountable owner to each use, record what data it touches, and tie it to a risk assessment. This inventory is the basis for the controls and evidence that follow.
What controls and evidence apply to AI governance?
Controls typically cover AI use policies, risk assessments, access and data handling, vendor and third-party review, and incident handling. Evidence shows those controls exist and operate, such as an AI inventory, documented approvals, review records, and monitoring outputs.
How do you prove AI controls are actually working?
Having a framework or policy shows intent. Proving effectiveness requires evidence that controls operate over time: continuous monitoring, regularly collected evidence, and expert review of risk. That is the shift from "we have a framework" to "we can prove it's working."