Research Progress on Decision-Right Allocation Mechanisms and Value Co-Creation in Human-AI Collaborative Creative Production

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

Continuous advances in generative artificial intelligence (Gen AI), multimodal large language models (MM-LLMs), and agent technologies are transforming creative work from a model in which humans use tools into one in which humans and artificial intelligence (AI) jointly define problems, generate alternatives, and refine outcomes. These capabilities accelerate content production while shifting the power to propose ideas, generate alternatives, evaluate and revise content, make final decisions, and assume responsibility from individual creators toward intelligent systems and platforms. Using thematic synthesis and mechanism analysis, this review examines research published from 2024 to 2026 across four dimensions: technological evolution, collaboration modes, decision-right allocation, and value co-creation. On this basis, it proposes a five-dimensional model comprising goal setting, proposal generation, evaluation and selection, revision and refinement, and responsibility, together with an analytical framework spanning capability complementarity, interactive collaboration, and value creation. Decision rights should not be divided once and for all. AI may receive greater operational authority when model capability and traceability are high, but value objectives, final selection, and responsibility must remain under human control. Future research should shift from static division of labor to process governance and build a human-AI creative governance system in which decisions are transparent, contributions are traceable, outcomes are contestable, and benefits can be allocated.