Generative AI skills and culture for security organizations
summary
AWS security team builds a people-first GenAI program that targets upskill 100% of staff, couples in-house training with selective external hires (McKinsey: 57% in-house, 30% external, 13% undecided), and runs weekly demos and experiments to turn learning into product-ready features. They create an ML Security Ambassador Program to scale with limited bandwidth, track progress via weekly/monthly business reviews and KPIs, and point to hands-on resources like CodeWhisperer and Bedrock and Amazon Queue.
AI-written summary · about
chapters (9)
- 0:00Introduction and context
- 1:53Addressing the skills gap
- 3:59Defining organizational strategy
- 4:53Implementation plan
- 7:08Execution and communication
- 10:17Pillars of AI success
- 16:35Lessons learned and adaptation
- 17:04Resources and concluding remarks
- 17:39Closing
related talks
44mGenerative AI Security — A Practical Guide to Securing Your AI Application
43mRethink how you develop with Generative AI tools
23mGenerative AI use cases
28mSecuring AI by design
37mInnovate Responsibly with Generative AI
46mBest Practices for Industrializing Responsible Generative AI
29mIndustry generative AI in action
46mThe Augmented Developer: Use Generative AI
