AI Hot Topics: The Data Behind AI: From Enterprise Data to Ground Truth

Please join the Data Science and AI Academy for the AI Hot Topic series, an opportunity for people curious about AI to network with experts, scholars and practitioners. Each month, a small group from industry and academia will explore a new topic in AI research, ethics, and practice. Through these conversations, we will envision new opportunities to build industry-academia-government partnerships, collaborations, and community.

Title: The Data Behind AI: From Enterprise Data to Ground Truth

Description: AI models are becoming more capable, but their usefulness ultimately depends on the data they learn from, the context they can access, and how we determine what is correct.
This panel explores the data foundation of AI—from the vast amounts of structured and unstructured data inside enterprises to the specialized datasets required to train, fine-tune, evaluate, and improve AI models. We will examine the increasingly important role of ground truth and human expertise: who determines what is correct when experts disagree, how human judgment and bias enter AI systems, and whether synthetic and AI-generated data can supplement—or eventually replace—human-generated data.
The discussion will also address the risks that emerge as AI becomes embedded in consequential workflows: data quality and provenance, privacy and intellectual property, hallucinations, bias, model evaluation, and the appropriate role of human oversight.