Supervised AI Workflow for Media Sales

Session details:

This paper presents a flexible, AI-augmented media sales workflow architecture designed to increase the speed, accuracy, and strategic quality of responses to media Requests for Proposals (RFPs). The system integrates multiple specialized AI agents with human sales oversight, creating a collaborative framework in which AI handles high-volume analysis and proposal generation while sales professionals retain control over judgment-critical decisions. RFPs sourced from email, voicemail, automated platforms, or direct inputs are automatically ingested and evaluated by AI agents that identify missing information, raise issues, generate clarifying questions, and produce optimized initial proposals. A unified sales dashboard provides real-time visibility into each RFP’s status, enabling sales teams to quickly resolve blockers, approve outbound communications, or delegate routine steps back to the AI. The architecture introduces a dynamic approval model that allows AI agents to autonomously respond to low-risk inquiries or deliver standard proposals, while routing more nuanced or strategically sensitive interactions for human review. By balancing automation with human expertise, the workflow reduces turnaround time, improves proposal consistency and quality, minimizes manual effort, and strengthens client responsiveness. This paper details the underlying components, decision frameworks, and operational benefits of this hybrid AI-human media sales workflow, demonstrating its potential to transform the efficiency and effectiveness of modern media sales organizations.