Topic & Goal
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 and 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.
Important Dates
- Submission Deadline: 20 Aug, 2026
- Paper Notification: 18 Sep, 2026
- Camera Ready Deadline: 05 Oct, 2026
All submission deadlines are at 23:59 in Anywhere on Earth (AoE) time zone(UTC-12).
Acknowledgement
The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft, covering all expenses, including costs for Azure cloud services as well as software development and support.