{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T00:53:41Z","timestamp":1780448021922,"version":"3.54.1"},"reference-count":72,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T00:00:00Z","timestamp":1771977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Agentic AI is increasingly framed as enabling consumers to delegate commerce decisions and actions to digital assistants, yet consumer-facing evidence still centers on assistive chatbots and recommender-like systems, with scarce evaluation of execution-level delegation. This study provides an evidence-mapping review of empirical work on agentic commerce and synthesizes determinants and outcomes of delegation across three questions: (RQ1) how systems are operationalized (autonomy, task scope, interaction mode, and transaction capability\/evidence realism), (RQ2) what facilitates or inhibits delegation, and (RQ3) what downstream outcomes follow for marketing performance and consumer experience. We searched Scopus and Web of Science for English-language, peer-reviewed primary studies (2015\u20132026) and applied conservative coding rules that distinguish claimed capability from simulated or demonstrated execution. The mapped literature is concentrated in text-based, low-autonomy assistants focused on recommendation and post-purchase support; coverage drops sharply for workflow-level autonomy, cart building, checkout\/payment execution, and negotiation. Across studies, findings cluster into two motifs: a utility\/assurance pathway in which performance cues and interaction quality increase perceived usefulness, satisfaction, and trust, and a governance pathway in which autonomy cues and system-initiated control trigger reactance\/powerlessness and reduce acceptance unless mitigated by safeguards; urgency can attenuate governance resistance. Because most outcomes are intention- or vignette-based, calibration, verification, and error-recovery behaviors remain under-measured. Overall, delegation appears to depend less on maximizing autonomy than on coupling capability with user governance (consent, oversight, recourse, accountability), and we outline measurement priorities for evaluating execution-capable agents.<\/jats:p>","DOI":"10.3390\/info17030222","type":"journal-article","created":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T09:31:32Z","timestamp":1772098292000},"page":"222","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2444-9796","authenticated-orcid":false,"given":"Stefanos","family":"Balaskas","sequence":"first","affiliation":[{"name":"eGovernment & eCommerce Lab (Innovation & Entrepreneurship), Department of Business Administration, University of Patras, 26504 Patras, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2426","DOI":"10.1108\/IMDS-04-2024-0329","article-title":"Why People Trust AI Software Robots: A Mediated Moderation Perspective on the Interaction between Their Intelligence and Appearance","volume":"125","author":"Kim","year":"2025","journal-title":"Ind. 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