What: “Agentic” systems refer to digital systems that can independently interact in a dynamic world.

Why is it important: The next generation of AI transformation is likely to be led by agents that use foundation models to execute complex, multistep workflows across a digital world.

Agentic systems traditionally have been difficult to implement, requiring laborious, rule-based programming or highly specific training of machine-learning models. However, when agentic systems are built using foundation models (which have been trained on extremely large and varied unstructured data sets) rather than predefined rules, they have the potential to adapt to different scenarios in the same way that LLMs can respond intelligibly to prompts on which they have not been explicitly trained.

The article details several use cases, one of them being online marketing campaign creation. A potential agent-based solution could be to help develop, test, and iterate different campaign ideas as well as tap online surveys, analytics from customer relationship management solutions, and other market research platforms aimed at gathering insights to craft strategies to create inputs for content creation agents. These would collaborate to iterate and refine outputs and align toward an approach that optimises the campaign’s impact while minimising brand risk.

Why agents are the next frontier of generative AI