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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">mir</journal-id><journal-title-group><journal-title xml:lang="ru">МИР (Модернизация. Инновации. Развитие)</journal-title><trans-title-group xml:lang="en"><trans-title>MIR (Modernization. Innovation. Research)</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2079-4665</issn><issn pub-type="epub">2411-796X</issn><publisher><publisher-name>School of Public Administration</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18184/2079-4665.2026.17.3.396-416</article-id><article-id custom-type="edn" pub-id-type="custom">bnjbgm</article-id><article-id custom-type="elpub" pub-id-type="custom">mir-2306</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>МОДЕРНИЗАЦИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>MODERNIZATION</subject></subj-group></article-categories><title-group><article-title>Генеративный ИИ как вторая волна когнитивной экстернализации</article-title><trans-title-group xml:lang="en"><trans-title>Generative AI as the second wave of cognitive externalization</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4033-2937</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Сидорчук</surname><given-names>Р. Р.</given-names></name><name name-style="western" xml:lang="en"><surname>Sidorchuk</surname><given-names>R. R.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Сидорчук Роман Роальдович, доктор экономических наук, доцент, профессор кафедры маркетинга Российского экономического университета им. Г. В. Плеханова; Почетный работник сферы образования РФ</p><p>Москва</p><p>Scopus ID: 56426297800</p><p>Researcher ID: D-4239-2009</p></bio><bio xml:lang="en"><p>Roman R. Sidorchuk, Doctor of Economic Sciences, Associate Professor, Professor of the Marketing Department, Plekhanov Russian University of Economics; Honorary Worker of Education of the Russian Federation</p><p>Moscow</p><p>Scopus ID: 56426297800</p><p>Researcher ID: D-4239-2009</p></bio><email xlink:type="simple">Sidorchuk.rr@rea.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Российский экономический университет им. Г. В. Плеханова</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Plekhanov Russian University of Economics</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>03</day><month>09</month><year>2026</year></pub-date><volume>17</volume><issue>3</issue><fpage>396</fpage><lpage>416</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Сидорчук Р.Р., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Сидорчук Р.Р.</copyright-holder><copyright-holder xml:lang="en">Sidorchuk R.R.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.mir-nayka.com/jour/article/view/2306">https://www.mir-nayka.com/jour/article/view/2306</self-uri><abstract><sec><title>Цель</title><p>Цель. В статье уточняются теоретические и методические основания интерпретации генеративного искусственного интеллекта (ГИИ) как второй волны когнитивной экстернализации в раскрытии организаци онно-экономических и маркетинговых следствий этого процесса.</p></sec><sec><title>Методы</title><p>Методы. Исследование выполнено как систематизированный концептуально-интегративный обзор с использованием логики PRISMA для прозрачности поиска, очистки и отбора источников. Сопоставлены корпуса публикаций по письменности и ГИИ в международных базах данных статей; проведен контрольный полнотекстовый поиск в базе Российского индекса научного цитирования. Источники анализировались с учетом их теоретической плотности, описания внешней когнитивной функции и пригодности для экономико-маркетинговой интерпретации.</p></sec><sec><title>Результаты работы</title><p>Результаты работы. Показано, что когнитивная разгрузка является частным механизмом снижения нагрузки на память, внимание и первичную обработку информации, тогда как когнитивная экстернализация описывает более широкий перенос когнитивных функций во внешние знаковые, материальные и вычислительные системы. Письменность закрепила внешнюю память и повторный доступ к смыслу; ГИИ включается в промежуточные операции интеллектуального труда: формирование задачи, критериев, альтернатив, аргументации и предварительной рамки решения. Тем самым меняется не только скорость подготовки текста, но и распределение ответственности за постановку задачи, проверку ре зультата и выбор.</p></sec><sec><title>Выводы</title><p>Выводы. Предложенная интерпретационная рамка позволяет рассматривать ГИИ как внешнее процедурное опосредование. Для маркетинга это означает изменение компетенций, работы с рыночной ин формацией, интерфейсов выбора и механизмов формирования ценности. Практические выводы требуют дальнейшей эмпирической проверки в организациях, маркетинговых подразделениях и на отраслевых рынках.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Purpose</title><p>Purpose: to clarify the theoretical and methodological grounds for interpreting generative artificial intelligence (GenAI) as the second wave of cognitive externalization and to reveal the organizational and economic and marketing consequences of this process.</p></sec><sec><title>Methods</title><p>Methods: the study is designed as a systematized conceptual and integrative review and uses PRISMA logic to ensure transparency of the source search, cleaning and selection. Two bodies of literature – on writing and on GenAI – are compared in international article databases; an additional full-text control search was conducted in the Russian Science Citation Index. The sources were analyzed taking into account their theoretical density, cognitive function and suitability for economic and marketing interpretation.</p></sec><sec><title>Results</title><p>Results: cognitive offloading is shown as a mechanism for reducing the load on memory, attention and primary information processing, whereas cognitive externalization describes a broader transfer of cognitive functions into external symbolic, material and computational systems. Writing established external memory and repeated access to meaning; GenAI becomes involved in intermediate operations of knowledge work: task framing, criteria formation, generation of alternatives, argumentation and preparation of a preliminary decision framework. Thus, not only the speed of text production changes, but also the distribution of responsibility for task framing, result verification and choice.</p><p>Conclusions and Relevance: the article proposes an interpretive framework that allows considering GenAI as external procedural mediation. For marketing, this means changes in professional competences, work with market information, choice interfaces and value formation mechanisms. The practical implications require further empirical testing in organizations, marketing departments and sectoral markets.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>генеративный искусственный интеллект</kwd><kwd>ГИИ</kwd><kwd>когнитивная экстернализация</kwd><kwd>когнитивная разгрузка</kwd><kwd>внешнее процедурное опосредование</kwd><kwd>маркетинг</kwd><kwd>экономика знаний</kwd></kwd-group><kwd-group xml:lang="en"><kwd>generative artificial intelligence</kwd><kwd>GenAI</kwd><kwd>cognitive externalization</kwd><kwd>cognitive offloading</kwd><kwd>external procedural mediation</kwd><kwd>marketing</kwd><kwd>knowledge economy</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Noy S. Experimental evidence on the productivity effects of generative artificial intelligence // Science. 2023. Vol. 381. Iss. 6654. 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