Proactive Hybrid Recommendation Audio Advertising in Generative AI Conversations: An AI-Initiated Audio Advertising Format Integrating Organic and Sponsored Recommendations
Year: 2026
Type: preprint
Abstract: This paper proposes Proactive Hybrid Recommendation Audio Advertising (PHRAA), a conceptual advertising framework designed specifically for audio-based interactions with generative artificial intelligence (AI). PHRAA enables a generative AI system to autonomously initiate an audio recommendation sequence when the conversational context indicates a potentially appropriate opportunity, without requiring the user to explicitly request product recommendations, service suggestions, or advertisements in the current interaction. The proposed format integrates two distinct categories of recommendations into one coherent audio presentation: organic audio recommendations, which are selected or generated according to their contextual relevance and potential usefulness to the user without being included as a result of payment for placement, and sponsored audio recommendations, which are included through paid advertising or commercial sponsorship arrangements and are explicitly identified as such. The defining characteristic of PHRAA is that the entire AI-initiated hybrid audio recommendation sequence constitutes a single, identifiable advertising unit. It is therefore conceptually different from inserting an isolated audio advertisement into a conversation, playing a conventional pre-roll or mid-roll advertisement, or presenting sponsored recommendations only after a user explicitly requests product suggestions. The framework introduces a proactive opportunity assessment mechanism, a dual-source recommendation selection process, a hybrid audio sequence construction mechanism, sponsorship disclosure and classification controls, and user-autonomy safeguards. It also establishes operational principles for audio timing, recommendation ordering, voice presentation, interruption management, and conversational continuity. Importantly, PHRAA does not assume that the integration of organic and sponsored recommendations automatically improves advertising effectiveness or user experience. Instead, it establishes a testable framework through which these outcomes can be investigated. By defining the complete AI-initiated hybrid audio recommendation sequence as the advertising unit, this paper provides a distinct conceptual foundation for proactive audio advertising in generative AI conversations and identifies the technical, behavioral, commercial, and ethical questions that future implementations must address.
Author: Zhang, Jincheng
Language: English
Topic: AI in Service Interactions
Subfield: Marketing
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7225758276
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