This chapter examines how intelligent technologies are restructuring language service management and operations. It frames modern workflows as modular, node‑based systems in which process nodes (ingestion, preprocessing, assignment, execution, consolidation, feedback) are dynamically reconfigurable and instrumented with quality, time, and risk indicators. Large Language Models and agent architectures shift coordination from file‑centric handoffs to semantic connectivity, enabling context graphs, automated resource orchestration, and adaptive scheduling. Business models evolve from labor and per‑word pricing to platform productization, capability‑bundled, risk‑aware pricing, and data asset monetization. Client management expands beyond textual quality toward experience visibility, customization, lifecycle communication, and retention analytics. Team structures move from discrete translator–editor roles to hybrid human–AI collaboration, adding new functions (prompt engineering, data stewardship, workflow orchestration). Operational intelligence rests on governed linguistic/data assets, modular platform integration, and observability pipelines that capture micro‑behaviors, power experimentation (A/B, canary deployment), and drive algorithmic feedback loops for continuous optimization. The chapter highlights systemic thinking, data governance, and human value amplification as emerging differentiators in a platform‑anchored, AI‑mediated ecosystem.