Decision support and optimization
Having explored the physical world applications of agentic systems, we now turn to their role in augmenting human decision-making and solving complex optimization problems. While traditional decision support systems rely on fixed rules and static analysis, LLM-based agents can understand context, reason about trade-offs, and provide adaptive recommendations while maintaining alignment with business objectives and constraints.
Evolution of decision support agents
The integration of LLMs with decision support systems has transformed how organizations process information and make strategic choices. Modern decision agents can analyze multiple data streams, understand complex business contexts, and generate actionable insights while maintaining awareness of organizational goals and constraints. Key capabilities that distinguish modern decision support agents are as follows:
- Multi-modal data analysis and synthesis
- Context-aware recommendation...
