Profitability in the Synthetic Era: 19 11
The Hybrid SinergIA Model as a Catalyst for the Commercial Ecosystem, GEO, and Competitive Advantage
DOI:
https://doi.org/10.51896/2a1chh43Keywords:
Artificial intelligence, Marketing, Ethics of technology, social media, Electronic commerce, ConsumerAbstract
Who should a piece of content convince today? The human audience, or the language model that decides whether humans even see it? What separates a brand that survives the saturation of synthetic content from one that dissolves into it? The questions are not rhetorical. Every technology that cheapened content production -the printing press, radio, the internet- triggered the same sequence: abundance, saturation, and a new scarcity, this time of trust. Generative artificial intelligence repeats the pattern at unprecedented scale. Pophal (2026)calls the result "AI Slop," and in doing so names a deeper shift; The axis of competitiveness in digital marketing is moving from production to recognition. Producing content is no longer enough; organizations must hold epistemic authority before generative AI systems, not only before the human consumer. This article proposes the Hybrid SynergIA Model(HSM), a three-dimensional framework -human, AI-analytical, and ethical-contextual- derived from a systematic integrative synthesis of 16 empirical studies (2025-2026), with validated inter-rater coding(Cohen's κ = 0.87). The results show that coordinated interaction among the HSM's three dimensions generates multiplicative effects on organizational profitability, distinct from those produced by AI operating alone: there, short-term gains in volume coexist with eroding trust and rising brand abandonment. AI technology is already an infrastructure commodity; sustainable competitive advantage now resides in the deliberate governance of its integration with human judgment. The HSM positions Generative Engine Optimization (GEO)as its strategic frontier dimension, in line with Service-Dominant Logic (Vargo & Lusch, 2004, 2008) and Dynamic Capabilities theory (Teece et al., 1997).
Downloads
References
Ash Shiddieqy, A. Z., & Widarmanti, T. (2025). The influence of artificial intelligence in digital marketing on Generation Z consumer decision making. Eduvest, 5(9), 10701-10718. https://doi.org/10.59188/eduvest.v5i9.51509
Beyari, H., & Hashem, T. (2025). The role of artificial intelligence in personalizing social media marketing strategies for enhanced customer experience. Behavioral Sciences, 15(5), Article 700. https://doi.org/10.3390/bs15050700
Calanchez Urribarril, Á., Boscán Carroz, M., Chávez Vera, K. J., & Zambrano Verdesoto, G. J. (2025). Netnografía en el marketing digital: un análisis de aplicaciones, retos y técnicas emergentes. Revista Lasallista de Investigación, 22(2), 263-279.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Harun, M. F., Al Bakry, N. S., Tazilan, A., Abdullah, Y., & Hashim, M. E. A. H. (2025). Leveraging artificial intelligence in advertising: A systematic literature review. paperASIA, 41(5b), 410-424. https://doi.org/10.59953/paperasia.v41i5b.763
Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. https://doi.org/10.2307/1914185
Kapoor, P., Balaji, M. S., & Maity, M. (2026). Game on: Enhancing customer engagement through influencers' gamified messages. Journal of Travel Research, 65(1), 37-56. https://doi.org/10.1177/00472875241289565
Kumar, S., Malhotra, D., & Kathuria, G. (2025). Artificial intelligence research in social media marketing: A review, synthesis and research avenues. Journal of Global Marketing. Advance online publication. https://doi.org/10.1080/08911762.2025.2593340
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE.
Loza, R., & Romaní, G. (2026). Social media marketing, purchasing decisions, and consumer satisfaction in Peruvian millennials. TEC Empresarial, 20(1), 22-47. https://doi.org/10.18845/te.v20i1.8393
Mehmood, K., Nisar, Q. A., Albishri, N., Agarwal, S., & Tamás, V. (2026). The psychology of online shopping success: Insights on social media analytics and customer feedback. Acta Psychologica, 264, Article 106329. https://doi.org/10.1016/j.actpsy.2026.106329
Nunes, D. C., Schmidt, S., Crespo, C. F., & Eberle, L. (2025). Moderation and/or mediation? The role of engagement in relationship quality and customer loyalty. Journal of Relationship Marketing, 24(2), 148-172. https://doi.org/10.1080/15332667.2024.2405309
Oleksiuk, A. (2025). Artificial intelligence in global marketing campaigns: Between human creativity and algorithmic precision. Vezetéstudomány / Budapest Management Review, 56(12), 56-67. https://doi.org/10.14267/VEZTUD.2025.12.05
Oliveira, H. Z., & Lima, H. (2025). AI and marketing: Bridging the gap through a game-based tool among higher education students. Comunicar, 33(82), 138-151. https://doi.org/10.5281/zenodo.16123256
Pilelienė, L., & Bogoyavlenska, Y. (2025). Artificial intelligence in influencer marketing: Current researchscape, trends and insights from a bibliometric review. Equilibrium. Quarterly Journal of Economics and Economic Policy, 20(2), 583-611. https://doi.org/10.24136/eq.3783
Pophal, L. (2026). Marketing's age of AI has arrived, now comes the hard part. Customer Relationship Management, April, 20-23.
Sahut, J.-M., & Laroche, M. (2025). Using artificial intelligence (AI) to enhance customer experience and to develop strategic marketing: An integrative synthesis. Computers in Human Behavior, 170, Article 108684. https://doi.org/10.1016/j.chb.2025.108684
Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z
Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing, 68(1), 1-17. https://doi.org/10.1509/jmkg.68.1.1.24036
Vargo, S. L., & Lusch, R. F. (2008). Service-dominant logic: Continuing the evolution. Journal of the Academy of Marketing Science, 36(1), 1-10. https://doi.org/10.1007/s11747-007-0069-6
Venith Vijay, M., Selvaraj, V., Muzhumathi, R., & Sundara BalaMurugan, P. (2025). Leveraging strategic marketing analytics to drive competitive advantage in data-driven markets. Archives for Technical Sciences, 17(34), 647-659. https://doi.org/10.70102/afts.2025.1834.647
Wang, J., & Yu, L. (2025). Application and practice of artificial intelligence in marketing strategy. Discover Artificial Intelligence, 5(1), Article 103. https://doi.org/10.1007/s44163-025-00346-1
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

