AI often looks great in demos, but things change once it’s used in real systems. This panel is about what actually happens when AI is deployed in applications and software development.

The discussion will focus on everyday challenges teams face, such as dealing with messy data, scaling AI services, and keeping systems reliable as users and behaviour change. I will share real experiences from building and running AI systems, including what worked, what didn’t, and what they would do differently.

Instead of focusing on models or theory, the session will look at the practical side of AI in production. The goal is to help engineers and technical leaders better understand the trade-offs involved in building AI systems that work reliably in real-world environments.

This session is for anyone working with AI in development who wants a clearer picture of what “AI in production” really means.