Autonomy Budget Allocation

Autonomy Budget Allocation treats each conversational agent deployment as a finite budget of unattended decisions, not a binary switch between bot and human. Every workflow gets a ceiling: how many turns, which intents, and which dollar thresholds the agent may resolve without a person. Spend the budget where deflection is cheap and reversible (order status, hours, password resets) and reserve human capacity for intents with refund, legal, or churn exposure. Agencies that price retainers on this model can show clients a defensible cost per resolved contact instead of a flat seat count. Forrester found 83% of B2C marketing decision makers already work with AI agents, so the differentiator is no longer deployment but governance of where autonomy stops. A travel client using Skye-style natural language booking, for example, should cap the agent at itinerary search and route any fare change or cancellation to a human, because a misread date costs more than the deflection saves.