Breaking down societal challenges into smaller roles and tasks allows AI systems to coordinate multi-step reasoning and match specific company capabilities to distinct problem components.

Agentic AI architectures use symbolic reasoning, language model-based chain-of-thought, and planning algorithms to decompose big issues into manageable parts. These roles can then be matched with companies’ specialized data and competencies, enabling targeted, proactive problem-solving rather than blunt, one-size-fits-all approaches.