Agentic data science with the Data Agent Kit
cloud.google.com·8h ago
AI Research
arXiv CS.AI·Aug 7·5 min read
When Agentic AI Meets Integrated Sensing and Communication
TL;DR
Agentic AI is evolving Integrated Sensing and Communication (ISAC) into a goal-driven intelligent system, termed AISAC, which enhances multimodal intelligence and network management. This framework reveals gaps in agentic maturity and identifies critical challenges in AI integration.
✦ Why It Matters
Evaluate your current AI systems against the nine agentic-specific criteria to identify maturity gaps.
Key Takeaways
- Assess your AI systems for agentic maturity using the provided framework.
- Explore advancements in multimodal intelligence for improved network management.
- Address privacy and security in AI applications to enhance resilience.
- Investigate challenges in predictive modeling and multi-agent collaboration.
Full Summary
Agentic artificial intelligence (AI) is reshaping Integrated Sensing and Communication (ISAC) into a more intelligent, goal-oriented system, referred to as AISAC. This survey consolidates various research areas, including learning-based sensing and multi-agent coordination, into a six-stage closed-loop framework: observation, contextualization, reasoning and prediction, planning and orchestration, execution and collaboration, and feedback and resilience.
Five levels of agentic maturity are introduced, highlighting the transition from basic physical-layer functions to fully autonomous systems. The review covers advancements in multimodal intelligence, large language models, and AI-native network management, while also addressing privacy, security, and sustainability concerns.
An audit of existing studies against nine evaluation criteria reveals that no system meets more than two, indicating a significant gap in achieving true agentic maturity. Key challenges include developing predictive models and ensuring safe multi-agent collaboration.