Lloyd Blankfein, former CEO of Goldman Sachs, shares insights on leadership in crisis, the philosophy of risk management, and the evolution of institutional culture. He discusses navigating the 2008 financial crisis, the transition from a partnership to a public company, and the profound impact of technology and AI on finance and risk.
Variance, emerging from three years in stealth with a $21 million Series A, is transforming enterprise risk and compliance through purpose-built AI agents. Founded by ex-Apple engineers, the company automates complex tasks like fraud detection, content review, and identity verification for Fortune 500s and platforms such as GoFundMe. They discuss the strategic reasons for stealth, technical challenges of integrating disparate data sources (including UI scraping), the shift from legacy systems to self-healing AI agent architectures, and how their lean, AI-maximalist team detects sophisticated threats like state-sponsored fraud rings.
In this interview, Sarah Wells and Nick Selby discuss the significant business risks introduced by the current rush to adopt AI. They cover how AI vendors blur security terminology, how the insatiable need for data creates an enormous blast radius for breaches, and provide a framework for responsible AI adoption through threat modeling, cross-disciplinary governance, and a return to IT fundamentals.
Explore the significant security risks posed by Agentic AI and quantum computing, from data breaches of sensitive information to the breakdown of modern cryptography. Learn proactive strategies for governing AI and preparing for a quantum-safe future.
The video explains the distinct but complementary roles of AI governance and security in mitigating AI risks. It contrasts their focuses, from self-inflicted policy violations (governance) to intentional external attacks (security), and proposes a layered framework combining both for comprehensive protection.
Ben Lorica and David Talby of 'The Data Exchange' podcast analyze the 2025 AI Governance Survey, revealing a significant gap between AI adoption and mature risk management. While 30% of organizations have models in production, many lack robust governance frameworks, incident response plans, and comprehensive monitoring, often prioritizing speed-to-market over safety and compliance.