The Global Interpreter Lock (GIL) in Python limits concurrency performance by allowing only one thread to execute Python bytecodes at a time, impacting CPU-bound tasks. While threads struggle under the GIL for CPU-heavy workloads, I/O-bound tasks fare better as the GIL is released during I/O operations. Multiprocessing bypasses the GIL, enabling parallel execution across CPU cores. Utilizing threading, multiprocessing, or asyncio can optimize Python backend workloads depending on their nature.