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Journal of Information and Optimization Sciences cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Open Access Research Article

Business utility perception of brand and promotion consultancies toward AI applications : An empirical study

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pp. 3445–3454Vol. 47Issue 9-BSeptember 2026DOI: 10.47974/JIOS-2441XML
Received:
01 Jun 2026
Published Online:
30 Sep 2026
Article type:
Research Article
Language:
EN
Article no.:
JIOS-2441
Pages:
3445–3454

Abstract

AI is increasingly shaping the branding and promotional landscape for consultancy companies, and this study investigates how it impacts their operations. The study explores the impact of Artificial Intelligence (AI) on the branding and promotion consultancy landscape, considering its rising influence on the business. It illuminates the viewpoints of consultants, creatives, and agency managers regarding the capabilities of AI as a strategic tool, content generator, personalizer, campaign optimiser, and decision-maker. The results highlight a generally positive attitude towards AI, with significant interest in leveraging it for efficiency enhancement, insight creation, and tangible results. But issues of ethics, authenticity, and skill shortfalls remain a barrier to wider use. The research also shows that businesses with AI integration believe that it is more valuable to their companies than the companies that are not technologically prepared. The study helps to broaden the understanding of AI’s role in creative consulting and inform future capacity-building and ethical implementation of AI.

Keywords

Subject Classifications

68T0168T0568T0790B5091D30

References

[1] M.-H. Huang and R. T. Rust, “A strategic framework for artificial intelligence in marketing,” Journal of the Academy of Marketing Science, vol. 49, no. 1, pp. 30–50 (2021).

[2] A. Chauhan, S. Kumar, A. K. Karn, and S. Sharma, “Role of artificial intelligence in optimizing digital marketing: An empirical study,” Journal of Information and Optimization Sciences, vol. 46, no. 2, pp. 439–451 (2025).

[3] F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, vol. 13, no. 3, pp. 319–340 (1989).

[4] V. Venkatesh, J. Y. L. Thong, and X. Xu, “Consumer acceptance and use of information technology: Extending the unified theory,” MIS Quarterly, vol. 36, no. 1, pp. 157–178 (2012).

[5] J. Bughin, J. Seong, J. Manyika, M. Chui, and R. Joshi, “Notes from the AI frontier: Modeling the impact of AI on the world economy,” McKinsey Global Institute (2018).

[6] L. Floridi, J. Cowls, M. Beltrametti, R. Chatila, P. Chazerand, V. Dignum, C. Luetge, R. Madelin, U. Pagallo, F. Rossi, B. Schafer, P. Valcke, and E. Vayena, “AI4People-An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations,” Minds and Machines, vol. 28, no. 4, pp. 689–707 (Dec. 2018).

[7] J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, “When to use and how to report the results of PLS-SEM,” European Business Review, vol. 31, no. 1, pp. 2–24 (2019).

[8] J. F. Hair, G. T. M. Hult, C. M. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd ed. Sage Publications (2017).

[9] C. Fornell and D. F. Larcker, “Evaluating structural equation models with unobservable variables and measurement error,” Journal of Marketing Research, vol. 18, no. 1, pp. 39–50 (1981).

[10] The Processes of Technological Innovation L. G. Tornatzky and M. Fleischer, The Processes of Technological Innovation. Lexington, MA, USA: Lexington Books (1990).

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