Executives often see genAI as an instant awesome switch for their company. Their desire to use this technology overshoots its capabilities, leading to stalled projects and high-profile mishaps. Why does this keep happening? Why don't the execs see the danger signs? And what can you, the data practitioner, do about it? Using real-world genAI goofs, I'll share how to guide your stakeholders to better decisions and more successful rollouts. Who knows? You might talk them out of using AI altogether.

Q McCallum is a consultant, writer, and researcher. He's spent his career applying emerging and disruptive technology to business use cases. His consulting practice focuses on matters of strategy and risk management in machine learning and artificial intelligence

Q's written work includes Black Box Tactics: Use algorithmic trading techniques to improve your AI; Understanding Patterns of Disruption: Lessons Learned from the Cloud, Machine Learning, and More; Business Models for the Data Economy; Parallel R: Data Analysis in the Distributed World; and Bad Data Handbook: Mapping the World of Data Problems. He has been featured on O'Reilly Radar and publishes the Complex Machinery newsletter on the intersection of AI and risk.

Bluesky | Website | LinkedIn | Newsletter