A new architectural approach called agentic integration, enabled by the Model Context Protocol (MCP), allows AI agents to autonomously resolve complex, multi-system customer issues in real time. Amazon Connect Customer, the system of engagement, and Salesforce, the system of record, are connected through MCP to represent the leading edge of this shift. Rather than pre-coding every decision path into a contact flow, an orchestrator AI agent, powered by large language models (LLMs), dynamically determines which systems to engage, in what sequence, and continuously adapts its execution plan based on intermediate results. The agent reasons about the customer’s intent, chains actions across systems of record such as Salesforce, operational services, and knowledge bases, and resolves complex issues end to end. For decades, enterprise integration operated under the assumption that connectivity is a mechanical problem, with contact centers using static decision paths and prescribed API calls. The consequences of this old paradigm are significant: introducing a new backend system requires re-engineering the integration from the ground up, and modifying a workflow demands months of development.