AI is evolving from answering questions to autonomous agents that plan, decide, and execute tasks independently—soon extending to physical systems like robots and autonomous vehicles. The shift brings critical operational challenges: reasoning models and multi-agent systems consume 100-10,000x more compute tokens than basic generative AI. Organizations must balance capability, cost, and use-case fit by matching frontier models to complex tasks while using optimized open models for domain-specific workflows. The future workforce will blend human and digital agents working together.