Joe explores the transformative impact of AI on business processes, domains, and data modeling. He draws parallels to AlphaGo's surprising success against human players, highlighting a shift in how humans and machines will interact. As organizations begin adopting AI agents, the potential exists for these agents to create their own processes and domains, leading to what Joe calls "alien" systems that humans might struggle to comprehend. Current AI tools, including large language models (LLMs), have limitations, but advancements are happening rapidly. Joe notes that the temptation to deploy AI agents for continuous operation is strong, and as these agents multiply, they will likely enhance their capabilities. He contemplates the idea of "machine tacit" knowledge, where AI learns and optimizes processes in ways that are statistically efficient but not easily understood by humans. This evolution necessitates a reevaluation of data modeling. Instead of focusing solely on what has happened, future data models may need to emphasize the underlying reasons and mechanisms at play. Joe speculates that AI could create new data formats tailored to its requirements, moving away from traditional human-readable structures. The future may involve complex, dynamic data representations that adapt in real-time, challenging our current understanding of data systems.