Here we share insights emerging from our focused exploration of AI’s transformative role in business. These thought experiments aren’t destinations, but rather starting points for discovery and engineering.
Profiling—discovering the data patterns that define a customer, product, or other entity—is critical to many data science applications. Yet today it remains slow, manual, and reactive, poorly suited to a fast-moving business environment. When new threats or opportunities arise, data science teams often struggle to respond before the landscape changes again.
With large AI models and modern machine learning techniques, however, profiling can evolve into a continuous, real-time capability. Analysts and business teams gain rapid visibility into what sets a cohort apart, while systems scan for similar patterns across the entire database.
READ THE FULL ARGUMENTModern AI has become remarkably good at spotting patterns. But business needs are beyond prediction. They demand understanding.
At modell.ai, we believe the next leap forward in data science lies in moving beyond models that can only correlate, toward powerful causal models that explain, simulate, and guide action.
READ THE FULL ARGUMENTGot your own ideas about AI’s role in advancing data science? Let’s talk!