IEEE Big Data 2026 Workshop on Agentic AI for Big Data (AAI-BD 2026) will be held virtually on Dec. 14-16, 2026 in conjunction with IEEE Big Data 2026 and the Cross-AI Pre-Conference Symposium 2026 (https://cross-ai.io/conference/2027/preconf/).

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Introduction
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The rise of agentic AI marks a fundamental shift in how Big Data is leveraged and governed. By autonomously reasoning over vast and complex datasets, agentic AI moves Big Data beyond storage and analytics toward self-directed intelligence, enabling real-time insight generation, adaptive decision-making, and continuous evolution of data-driven systems at global scale.

AAI-BD is the first workshop in the world dedicated to this emerging area, bringing together leading researchers, practitioners, and industry experts to explore architectures, algorithms, and applications of autonomous AI systems for Big Data. It provides a high-impact forum to advance research, foster cross-disciplinary collaboration, and define the future of agentic AI in large-scale data-driven environments.

The workshop focuses on novel AI models, multi-agent systems, distributed AI architectures, and edge AI integration, with applications across domains such as finance, healthcare, IoT, robotics, smart cities, transportation, cybersecurity, environmental science, supply chain management, GIS, and creative and physical domains including arts, music, dance, and sports. It aims to spark discussion on scalable and autonomous AI systems, attract high-quality submissions bridging theoretical foundations and practical implementations, and highlight emerging challenges and transformative opportunities in the design, deployment, and evaluation of agentic AI systems.

Topics
This open call for papers invites original contributions on theory, methods, architectures, and applications of agentic AI for Big Data. Submissions may focus on technical, conceptual, or applied research, including but not limited to the areas below.

Technical topics and methods
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Architectures for agentic AI on Big Data
Autonomous multi-agent systems for data-intensive tasks
AI agents using distributed or NoSQL databases as memory
Integration of LLMs, generative AI, and multimodal AI in autonomous agents
Edge AI for real-time autonomous decision-making
Distributed and federated agentic AI systems
Agentic AI for autonomous data curation and cleaning
Explainability, interpretability, and trust in agentic AI systems
Evaluation frameworks, benchmarks, and performance metrics for agentic AI
Resource-efficient AI for large-scale data processing
Human-AI collaboration in autonomous systems
Security, privacy, and ethical considerations in agentic AI
Reinforcement learning and planning in multi-agent Big Data environments
Simulation-based testing for autonomous AI in data-rich contexts

Applications
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Robotics
Arts & Entertainment
Cybersecurity
Digital Content & Social Media
Finance
Internet of Things (IoT)
Transportation
Smart Cities
Geographic Information Systems (GIS)
Supply Chain & Logistics
Scientific Research
Environmental Science
Education

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Important Dates

Please visit the workshop website:
https://cross-ai.io/conference/2027/preconf/aaibd-2026/
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Submission

Please follow the workshop website to submit papers. Accepted papers will be published in the IEEE Big Data proceedings or Cross-AI proceedings.
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Google Group

Welcome to subscribe to our Google group (https://groups.google.com/g/multimodal-ai).