Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Artificial Intelligence Strategic Lifecycle: A Literature Review-Based Framework. / Ламбер, Жером Мишель Ж.; Гаранина, Ольга Леонидовна.
в: Review of Business and Economics Studies, Том 14, № 2, 25.07.2026, стр. 6-20.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Artificial Intelligence Strategic Lifecycle: A Literature Review-Based Framework
AU - Ламбер, Жером Мишель Ж.
AU - Гаранина, Ольга Леонидовна
PY - 2026/7/25
Y1 - 2026/7/25
N2 - Purpose. This systematic literature review examines how firms utilise artificial intelligence (AI) as a strategic rather than purely operational resource and develops an integrative conceptual framework of the AI strategic lifecycle. Design/methodology/approach. A PRISMA-guided search identified 147 peer-reviewed articles published between 2020 and 2025 across major scholarly databases, including Elsevier (Scopus), Emerald, Springer, and Wiley. The evidence is synthesised through five dominant theoretical lenses: dynamic capabilities, resource- based view (RBV), knowledge- based view (KBV), technology acceptance model (TAM), and disruptive innovation theory (DIT). Findings. Dynamic capabilities and RBV explain how organisations mobilise data, algorithms, and AI-related human capital to build and sustain competitive advantage in sectors such as public administration, energy, human resource management (HRM), and research-intensive industries. KBV highlights the role of absorptive capacity and knowledge- sharing routines in transforming AI outputs into innovation, particularly in user-facing contexts such as healthcare and hospitality. In these sectors, TAM is central, emphasising trust, ease of use, and perceived usefulness as key drivers of adoption. In finance, DIT elucidates competitive disruption and incumbent response strategies triggered by AI-enabled entrants. Practical implications. The review provides recommendations for practitioners, including investing in organisational learning and absorptive capacity and ensuring transparency of AI-enabled interfaces to translate AI investments into sustainable performance gains. Originality/value. By integrating five theoretical perspectives, the review develops a model of the AI strategic lifecycle, offering both a consolidated foundation for future research and a forward-looking agenda for managers seeking to leverage AI as a strategic asset.
AB - Purpose. This systematic literature review examines how firms utilise artificial intelligence (AI) as a strategic rather than purely operational resource and develops an integrative conceptual framework of the AI strategic lifecycle. Design/methodology/approach. A PRISMA-guided search identified 147 peer-reviewed articles published between 2020 and 2025 across major scholarly databases, including Elsevier (Scopus), Emerald, Springer, and Wiley. The evidence is synthesised through five dominant theoretical lenses: dynamic capabilities, resource- based view (RBV), knowledge- based view (KBV), technology acceptance model (TAM), and disruptive innovation theory (DIT). Findings. Dynamic capabilities and RBV explain how organisations mobilise data, algorithms, and AI-related human capital to build and sustain competitive advantage in sectors such as public administration, energy, human resource management (HRM), and research-intensive industries. KBV highlights the role of absorptive capacity and knowledge- sharing routines in transforming AI outputs into innovation, particularly in user-facing contexts such as healthcare and hospitality. In these sectors, TAM is central, emphasising trust, ease of use, and perceived usefulness as key drivers of adoption. In finance, DIT elucidates competitive disruption and incumbent response strategies triggered by AI-enabled entrants. Practical implications. The review provides recommendations for practitioners, including investing in organisational learning and absorptive capacity and ensuring transparency of AI-enabled interfaces to translate AI investments into sustainable performance gains. Originality/value. By integrating five theoretical perspectives, the review develops a model of the AI strategic lifecycle, offering both a consolidated foundation for future research and a forward-looking agenda for managers seeking to leverage AI as a strategic asset.
KW - artificial intelligence
KW - disruptive innovation
KW - dynamic capabilities
KW - innovation
KW - knowledge-based view
KW - resource- based view
KW - strategic management
KW - technology adoption
UR - https://www.mendeley.com/catalogue/da17d418-b6a7-39cc-ad5b-2bf7f68e517c/
U2 - 10.26794/2308-944X-2026-14-2-6-20
DO - 10.26794/2308-944X-2026-14-2-6-20
M3 - Article
VL - 14
SP - 6
EP - 20
JO - Review of Business and Economics Studies
JF - Review of Business and Economics Studies
SN - 2308-944X
IS - 2
ER -
ID: 158812733