Heritage and Sustainable Development | 2026
Authors: Wishah R.; Al-Sukkar A.S.; Dannoun Z.O.; Al Gaafreh J.M.; Qaimary S.; Rawashdeh L.
DOI: 10.37868/hsd.v8i1.1714
Journal: Heritage and Sustainable Development
Year: 2026
Publisher: Research and Development Academy
Document Type: Article
Open Access: All Open Access; Gold Open Access; Green Open Access
Cited by: 0
The meteoric rise of generative artificial intelligence (GenAI) has transformed marketing practices and business models for conducting businesses within the digital economy. GenAI exceeds its typical AI counterpart because besides analyzing data, it helps generate new text, images, and content with added features; therefore, an entirely new avenue for marketing innovation as well as organizational growth. This study aims to establish the relationship between the application of GenAI with marketing innovation and business growth through a mixed methods approach. Quantitative data analyzed by PLS-SEM was drawn from 180 respondents across diverse fields of marketing while qualitative insight was drawn from 12 semi-structured interviews with senior executives. The results indicated that the effects of GenAI adoption on marketing innovation ( β= 0.61, p < 0.001 ) and business growth ( β= 0.38, p < 0.01 ) were highly significant. Marketing innovation is also an intervening variable ( β= 0.32, p < 0.001 ). It has also been concluded that higher the company size and industry are, the stronger these connections will be. However, geography weakens their impact. Opportunities are identified qualitatively as personalization, cost efficiency, and rapid experimentation while challenges emerge in terms of privacy and ethical risks besides workforce resistance. This study extends the resource-based view, dynamic capabilities, and technology organization environment frameworks at a theoretical level and is actionable for managers and policymakers striving to create responsible GenAI adoption practices. © The Author 2026. Published by ARDA. This work is licensed under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) that allows others to share and adapt the material for any purpose (even commercially), in any medium with an acknowledgement of the work's authorship and initial publication in this journal.
Artificial intelligence; Business growth; Digital economy; GenAI; Marketing innovation