Who pays for the visibility-value gap on the agentic web

Parallel’s 2026 study argues that AI content markets face a “visibility-value gap,” in which domains frequently surfaced by AI systems may contribute less to answer quality than less-visible but more irreplaceable sources, measured using Shapley value, a game-theory method estimating each source’s marginal contribution. Based on one week of enterprise-skewed activity, the study identifies primary research, government records, and live inventory sites such as arxiv.org, fda.gov, and homedepot.com as underrated, while sites including Medium, Scribd, and ZipRecruiter appear comparatively overexposed because they are easier to substitute. It contends that attention-based measures such as traffic, citations, and crawls do not adequately compensate unique sources, while AI summaries and crawler activity can reduce publisher referrals and encourage publishers to block bots or impose paywalls, potentially weakening agent answers. The report proposes contribution accounting supported by provenance and source-level attribution, notes emerging licensing and transaction standards such as RSL and IAB CoMP, and presents Parallel’s Index platform as a planned marketplace that would measure domains’ visibility, uniqueness, and contribution to compensate publishers based on Shapley value rather than access or citation volume.

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