Understanding potential risks and challenges
The landscape of AI has evolved significantly with the emergence of large language models (LLMs) that power both generative AI and agentic systems. While generative AI focuses primarily on creating content based on prompts and patterns, agentic systems built on these same LLMs take this capability further by incorporating decision-making, planning, and goal-oriented behavior. This combination of generative capabilities with agency creates a powerful but potentially risky synergy.
Agentic systems leverage the generative capabilities of LLMs to not just produce content but also to actively analyze situations, formulate strategies, and take action toward specific objectives. This means that any inherent risks in generative AI systems – such as biases, hallucinations, or the generation of misleading information – become particularly critical when the system is empowered to act autonomously or semi-autonomously based on this...
