CTO to CTO: Building AI-Driven Systems 

AI experiments are everywhere. 
Reliable AI-driven systems in production are still rare. 

In this second session of the CTO to CTO series, senior technology leaders discuss what it actually takes to move from experimentation to building and operating AI-driven systems that deliver real business value. 

This is a live conversation between technology leaders responsible for delivery, cost, risk, and measurable outcomes. We’ll talk about the practical decisions CTOs face when AI moves from a promising idea into production systems. 

No hype. Just honest perspectives, real trade-offs, and lessons learned from building systems that have to work in the real world. 

What we’ll cover 

1. Preparing teams to build AI-driven systems 
What skills and roles are actually required when AI becomes part of production software systems. 

2. Hire or partner? 
When it makes sense to build internal AI capability - and when external expertise can help validate ideas before scaling teams. 

3. Choosing the right AI tech stack 
Should AI live inside your existing infrastructure (AWS, Azure, GCP), or should it evolve on a separate stack? Pros and trade-offs of both approaches. 

4. From prototype to production 
“It worked on my machine.” Why AI prototypes and weekend experiments often fail once they hit real infrastructure and scale. 

Why attend 

If you are responsible for engineering outcomes, budgets, and delivery reliability, this session will give you practical perspectives on how CTOs approach AI when it moves from experimentation to production systems.