Speaker Requests
If you want a talk/presentation on AI, Generative AI, and/or Large Language Models, emerging technologies, a motivational talk, or a workshop for your next gathering, school event, or healthcare event, we should talk. Just hit the contact Kerrie button.
Below are examples of the topics that I can address for presentations at various venues :
Speaking
Clear-Eyed AI Guidance for Organizations
After 55 years building technology systems—from mainframes to AI—I know the gap between vendor promises and reality. I've been through six hype cycles. I've watched systems work and fail in production at Google, IBM, Cisco, and Optum.
I don't give utopian AI pitches. I help organizations think clearly about what AI can actually do, what it can't, and what they should do about it.
Speaking Topics
What 55 Years of Building Tech Taught Me About AI Hype
The pattern repeats every technology cycle: impossible promises, breathless headlines, massive gap between demo and deployment. I've seen it six times. Here's how to recognize it, navigate it, and avoid expensive mistakes with AI.
Audience: General audience, technology leaders, executives
Preparing Students for an AI World
Not "everyone should learn to code AI." Real guidance on which skills remain valuable, how to teach critical thinking about AI and its outputs, and what students actually need to thrive in a world with AI tools.
Audience: Educators, administrators, and students
AI Reality Check: What Actually Works (And What Doesn't)
Not every AI application succeeds. Most fail quietly. Based on deploying AI at scale in healthcare and watching implementations across industries, here's what separates working systems from vaporware.
AI Fears: Real vs. Imagined—Why We're Worrying About the Wrong Things"
The real risk isn't AI becoming sentient, AGI, superintelligence, or destroying humanity—it's much closer to home. Truth is becoming a variable through deepfakes and AI-generated misinformation. Algorithmic bias is amplifying inequities, denying opportunities to those already disenfranchised. A handful of companies control the most powerful AI systems, so much for "democratizing AI." Add surveillance at scale and authoritarian regimes weaponizing these tools, and you have the actual AI threat landscape. Let’s focus on real, current risks we can actually address, not Hollywood scenarios.
Audience: General audience, policy makers, community leaders, and anyone anxious about AI safety
Audience: CTOs, product leaders, implementation teams
The 8 Types of AI: Stop Using It as a Suitcase Term
When someone says "AI is biased" or "AI will transform your business," ask: Which type of AI? This framework helps you think clearly about different AI systems, their capabilities, limitations, and appropriate use cases.
Audience: Business leaders, strategists, and anyone evaluating AI investments
Will AI Take Jobs? The Question Everyone's Asking the Wrong Question
AI doesn't threaten all jobs equally. It threatens jobs focused on creating assets (documents, code, images) far more than jobs that concentrate on solving problems in complex contexts. Here's how to evaluate your workforce's actual risk.
Audience: General audience, business leaders, executives
AI in Healthcare & LIFE SCIENCE: Separating Clinical Reality from Vendor Claims
I led AI engineering teams at Optum, deploying systems at scale. Here's what actually works in clinical settings, what fails, and how to evaluate vendor promises when lives are on the line.
Audience: Healthcare executives, clinical leaders, health IT professionals
From Mainframes to LLMs and Generative AI: An Engineer's Perspective on What's Different About AI
AI follows the same hype pattern as every technology I've built. But this time, two things are different: the fear is justified in new ways, and the misuse risks are real. Here's how to think about both.
Audience: Technology conferences, engineering leaders, CIOs
Architecting AI Systems: Beyond LLMs to Compound AI
Many organizations think "AI strategy" means "deploy ChatGPT." But production AI systems require much more: orchestrating multiple AI types (not just LLMs), integrating with existing infrastructure, handling failure modes, and building compound systems where different AI capabilities work together. Drawing on 55 years of architecting systems, from SOA to cloud to AI, here's how to think about AI as a systems engineering challenge, not just a model deployment problem.
Audience: Enterprise architects, CTOs, technical leaders, system designers
What Makes These Talks Different
Plain language for everyone. I explain complex AI concepts without jargon. Whether you're a CEO, teacher, parent, or frontline worker, you'll understand what I'm saying, no technical background required.
No vendor pitches. I don't sell AI products or services. I have no incentive to hype AI or fear-monger about it.
Pattern recognition for 55 years. I've built systems through every computing era. I've seen the hype cycle six times. I know the gap between promise and delivery.
Real implementation experience. I led AI teams deploying systems at scale in healthcare. I've watched systems work and fail in production. I know the difference between demos and deployment.
Speaking Credentials
National Inventors Hall of Fame Inductee (2025)
National Academy of Engineering Member (2023)
Former IBM Fellow (IBM's highest technical honor)
Former Google Executive
Former VP/CTO at Cisco
Led AI Engineering at Optum (UnitedHealth Group)
20+ patents across multiple computing eras
