AI API calls are I/O-bound — you're waiting on network responses. Async Python lets you run many AI requests concurrently, dramatically improving throughput. Here's how to build high-concurrency AI applications. Why Async for AI? A single AI API call might take 1-3 seconds. If you process 100 requests sequentially, that's 100-300 seconds. With async concurrency, you can process all 100 in seconds. `python import asyncio import httpx Sequential (slow) async def process_sequential(requests): results = [] for req in requests: result = await call_ai(req) # 2 seconds each results.append(result) return results Total: len(requests) × 2 seconds Concurrent (fast) async def process_concurrent(requests): tasks = [call_ai(req) for req in requests] results = await asyncio.gather(*tasks) return results Total: ~2 seconds total (all run in parallel) ` Basic Async AI Client `python import asyncio import httpx from typing import Optional class AsyncAIClient: def init(self, apikey: str, baseurl: str = "…