Single-agent AI handles tasks solo: decision-making, acting, executing. It works best for well-defined, simple problems. Multi-agent systems involve multiple agents collaborating, each specialising, which adds flexibility, fault tolerance, and scale. The trade-off is complexity in coordination, communication, and overhead. Picking the right model depends on task complexity, scalability needs.