Bruno Lecoq spent 20 years at Microsoft before founding BEMO, where he runs compliance and AI governance for small and medium businesses. In this episode he explains why blocking AI tools fails in practice - staff use them regardless - and what governing that use looks like: zero trust for smaller organisations, keeping AI costs under control as Microsoft's pricing shifts, and continuous compliance.

We also talk about where security teams go from here as AI picks up more of their work, and the new risks that arrive with the tools, deepfakes included. Bruno's examples come from his own clients - AI changing how departments work with each other, and how companies oversee what staff do with it.

Chapters

• 00:00 Introduction to BEMO and Cybersecurity
• 01:16 Understanding AI and Its Impact on BEMO
• 03:04 The Rapid Evolution of AI
• 04:33 AI's Impact on Work Environment and Governance
• 05:59 Organizational Changes and Convergence of Departments
• 09:36 Cross-Department Collaboration and Automation
• 13:19 Software Engineering and Security Concerns
• 16:45 Red Teaming and Agent Security Testing
• 20:57 Identity Management and Agent Actions
• 23:14 The Impact of the emdash
• 24:14 Security Challenges and Deep Fakes
• 25:28 Ensuring Authenticity in Hiring
• 26:27 Conditional Access and Verified ID Face Check
• 27:13 The Importance of Security and Compliance
• 30:15 The Significance of CMMC Compliance
• 31:17 The Role of Trust in the AI Era
• 37:23 The Digital Divide and Regulatory Challenges
• 39:08 Small to Medium Business Security and AI Adoption

Nema Sobhani, a data scientist at Avanade, discusses the concept of agents in AI and their impact on human activities. He explores the definition of agents, their role in the enterprise, and the ethical and social implications of their use. The conversation delves into the evaluation and governance of AI models, as well as the philosophical and practical considerations of human-AI interaction.

Takeaways

• Agents as AI entities are empowered to perform tasks autonomously, and they will increasingly become integral to various business functions, disrupting the org-chart.
• The evaluation and governance of AI models are crucial in ensuring their ethical, and responsible use in enterprise settings and as a key part of AI governance.

Chapters

• 00:00 Introduction to Agents in AI
• 07:58 Ethical and Social Implications of Agents
• 16:24 Evaluation and Governance of AI Models
• 26:20 Human Activities and the Role of AI

The conversation delves into the evolving landscape of AI and securing it, focusing on regulatory and legal drivers, the commoditization of AI, security & governance challenges, open source and commodification, and the nature of observability. Each chapter explores these themes in depth, providing valuable insights into the current state of AI technology and its impact on various industries.

Takeaways

• Regulatory and legal drivers to Agentic Security
• Are models being commoditised?
• Security and governance challenges
• Open Source
• Observability and security