Swarm-based algorithms are one of the most popular bio-inspired algorithms inspired by animals’ collective behavior. In this position paper, I discuss the benefits of how the self-adaptive community could benefit from considering bio-inspired algorithms in designing self-adaptive systems. I focus specifically on swarm-based algorithms where I discuss three main benefits: (i) utilizing swarm intelligence techniques for parameter optimization of the utility function in the design phase; (ii) enhancing MAPE-K loop with swarm-inspired algorithms in the run-time phase; (iii) emergent robust behavior as a byproduct of simple interactions among individual components.