Description

AI is transforming business, but it also introduces risks that traditional oversight methods weren’t built to handle. Boards and leadership teams are increasingly tasked with managing AI-driven risks, from compliance challenges to reputational concerns. 

In this session, we’ll break down how to evolve risk management and internal assessment practices to address the unique challenges of AI and generative AI. You’ll learn practical strategies for identifying vulnerabilities, aligning with emerging regulations, and building governance frameworks that enable responsible AI adoption. 

This talk is designed for business executives and data leaders looking to strengthen their AI risk management approach. We’ll cover key audit considerations, evolving standards, and the tools and credentials that can help position you as a trusted advisor in the AI era.


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Instructor's Bio

Cal Al-Dhubaib

Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company supporting over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in 2024. 

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications including Forbes, Nasdaq, VentureBeat, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, Technology Executive, and most recently 40 under 40.

Webinar

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    UPCOMING WEBINAR "Intro to AI Risk Management for Executives and Data Leaders"

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