Data & Database Systems for Modern AI

The rapid evolution of modern AI—driven by foundation models, large language models (LLMs), and autonomous agents—has fundamentally transformed the landscape of data management. AI is no longer a standalone paradigm; it is now deeply intertwined with data infrastructures that support large-scale retrieval, integration, and reasoning across heterogeneous, evolving data sources. As traditional database systems face unprecedented challenges in adapting to AI-native workloads, the International Workshop on Data & Database Systems for Modern AI (D2AI 2026) aims to explore the next generation of scalable, efficient, and trustworthy infrastructures.

Modern AI applications demand capabilities far beyond conventional processing, including hybrid retrieval (relational, vector, and graph), knowledge-grounded reasoning, and real-time data updates. D2AI 2026 provides a premier forum for researchers and practitioners from the fields of databases, machine learning systems, and AI infrastructure to exchange ideas and rethink core principles—such as indexing, query optimization, and provenance—in the context of AI-driven systems.

The workshop will be of significant interest to those developing data-centric AI solutions and AI-native database architectures. We welcome a diverse range of contributions, including regular research papers, vision papers highlighting future trends, and industry showcases that demonstrate real-world applications of AI-native data management.