Agentic AI

Autonomous AI agents capable of planning and executing complex tasks.
Agentic AI

Agentic AI refers to AI systems that can act autonomously to achieve goals, make decisions, and adapt their behavior based on experience and changing conditions. Unlike traditional AI that responds to specific inputs with predetermined outputs, agentic AI systems can plan, reason about goals, take actions, observe outcomes, and learning from results to improve future performance. These systems combine large language models, reasoning capabilities, tool use, and memory to create autonomous agents that can operate independently in complex environments.

The technology enables AI systems that can handle complex, multi-step tasks, adapt to new situations, and operate with minimal human oversight. Agentic AI can break down complex problems into steps, use tools and APIs to gather information or take actions, reason about the best approach, and learn from experience. Applications include autonomous trading systems that manage portfolios, AI assistants that can complete complex tasks independently, research agents that can investigate topics and synthesize findings, and systems that can operate and optimize processes autonomously. Companies like OpenAI, Anthropic, and various AI firms are developing agentic AI capabilities.

At TRL 6, agentic AI systems are being deployed in various applications, though reliability, safety, and control remain areas of active development. The technology faces challenges including ensuring agents act safely and within intended boundaries, handling unexpected situations, preventing harmful or unintended actions, and maintaining human oversight and control. However, as AI capabilities improve and safety measures develop, agentic AI becomes increasingly powerful. The technology could transform how AI is used by enabling systems that can operate autonomously, handle complex tasks end-to-end, and adapt to changing conditions, potentially automating complex workflows and decision-making processes while raising important questions about control, safety, and the role of human oversight in autonomous AI systems.

TRL
6/9Demonstrated
Impact
5/5
Investment
5/5
Category
Intelligence & Computation
Neuromorphic chips, photonic networks, quantum systems, autonomous software, edge AI, algorithmic breakthroughs.