Predictive AI and generative AI compete for attention and budgets – but they shouldn’t. They’re two distinct categories of enterprise ML use cases that solve different problems. Predictive AI improves existing large-scale operations, while genAI generates new content items and code, answers questions, serves as a thought partner, etc.

But a marriage of the two is ushering in new value propositions. For example, predictive AI promises to actualize genAI’s ambitious claims of potential autonomy (removing or reducing the human in the loop). And genAI improves the use of predictive AI by helping code it, helping explain it to stakeholders, and more.

That’s only the tip of the iceberg. Before track 2’s breakout sessions covering such hybrid approaches, come to this keynote session for Machine Learning Week Founder Eric Siegel’s overview of this trend.